Decrypting TLS traffic on BIG-IP
1 Introduction As soon as I joined F5 Support, over 5 years ago, one of the first things I had to learn quickly was to decrypt TLS traffic becausemost of our customers useL7 applications protectedby TLS layer. In this article, I will show 4 ways to decrypt traffic on BIG-IP, including thenew one just release in v15.xthat is ideal for TLS1.3 where TLS handshake is also encrypted. If that's what you want to know just skip totcpdump --f5 ssl optionsection as this new approach is just a parameter added to tcpdump. As this article is very hands-on, I will show my lab topology for the tests I performed and then every possible way I used to decrypt customer's traffic working for Engineering Services at F5. 2 Lab Topology This is the lab topology I used for the lab test where all tests were performed: Also, for every capture I issued the followingcurlcommand: Update: the virtual server's IP address is actually 10.199.3.145/32 2 The 4 ways to decrypt BIG-IP's traffic RSA private key decryption There are 3 constraints here: Full TLS handshake has to be captured CheckAppendix 2to learn how to to disable BIG-IP's cache RSA key exchange has to be used, i.e. no (EC)DHE CheckAppendix1to understand how to check what's key exchange method used in your TLS connection CheckAppendix 2to understandhow to prioritise RSA as key exchange method Private key has to be copied to Wireshark machine (ssldump command solves this problem) Roughly, to accomplish that we can setCache Sizeto 0 on SSL profile and remove (EC)DHE fromCipher Suites(seeAppendix 1for details) I first took a packet capture using :pmodifier to capture only the client and server flows specific to my Client's IP address (10.199.3.1): Note: The0.0interface will capture any forwarding plane traffic (tmm) andnnnis the highest noise to capture as much flow information as possible to be displayed on the F5 dissector header.For more details about tcpdump syntax, please have a look atK13637: Capturing internal TMM information with tcpdumpandK411: Overview of packet tracing with the tcpdump utility. Also,we need to make sure we capture the full TLS handshake. It's perfectly fine to captureresumed TLS sessionsas long as full TLS handshake has been previously captured. Initially, our capture is unencrypted as seen below: On Mac, I clicked onWireshark→Preferences: ThenProtocols→TLS→RSA keys listwhere we see a window where we can reference BIG-IP's (or server if we want to decrypt server SSL side) private key: Once we get there, we need to add any IP address of the flow we want Wireshark to decrypt, the corresponding port and the private key file (default.crtfor Client SSL profile in this particular lab test): Note:For Client SSL profile, this would be the private key onCertificate Chainfield corresponding to the end entity Certificate being served to client machines through the Virtual Server. For Server SSL profile, the private key is located on the back-end server and the key would be the one corresponding to the end entity Certificate sent in the TLSCertificatemessage sent from back-end server to BIG-IP during TLS handshake. Once we clickOK, we can see the HTTP decrypted traffic (in green): In production environment, we would normally avoid copying private keys to different machines soanother option is usessldumpcommand directly on the server we're trying to capture. Again, if we're capturing Client SSL traffic,ssldumpis already installed on BIG-IP. We would follow the same steps as before but instead of copying private key to Wireshark machine, we would simply issue this command on the BIG-IP (or back-end server if it's Server SSL traffic): Syntax:ssldump-r<capture.pcap>-k<private key.key>-M<type a name for your ssldump file here.pms>. For more details, please have a look atK10209: Overview of packet tracing with the ssldump utility. Inssldump-generated.pms, we should find enough information for Wireshark to decrypt the capture: Syntax:ssldump-r<capture.pcap>-k<private key.key>-M<type a name for your ssldump file here.pms>. For more details, please have a look atK10209: Overview of packet tracing with the ssldump utility. Inssldump-generated.pms, we should find enough information for Wireshark to decrypt the capture: After I clickedOK, we indeed see the decrypted http traffic back again: We didn't have to copy BIG-IP's private key to Wireshark machine here. iRules The only constraint here is that we should apply the iRule to the virtual server in question. Sometimes that's not desirable, especially when we're troubleshooting an issue where we want the configuration to be unchanged. Note: there is abugthat affects versions 11.6.x and 12.x that was fixed on 13.x. It records the wrong TLS Session ID to LTM logs. The workaround would be to manually copy the Session ID from tcpdump capture or to use RSA decryption as in previous example. You can also combine bothSSL::clientrandomandSSL::sessionidwhich isthe ideal: Reference: K12783074: Decrypting SSL traffic using the SSL::sessionsecret iRules command (12.x and later) Again, I took a capture usingtcpdumpcommand: After applying above iRule to our HTTPS virtual server and taking tcpdump capture, I see this on /var/log/ltm: To copy this to a *.pms file wecanuseon Wireshark we can use sed command (reference:K12783074): Note:If you don't want to overwrite completely the PMS file make sure youuse >> instead of >. The endresult would be something like this: As both resumed and full TLS sessions have client random value, I only had to copy CLIENT_RANDOM + Master secret to our PMS file because all Wireshark needs is a session reference to apply master secret. To decrypt file on Wireshark just go toWireshark→Preferences→Protocols→TLS→Pre-Master Key logfile namelike we did inssldumpsection and add file we just created: As seen on LTM logs,CLIENTSSL_HANDSHAKEevent captured master secret from our client-side connection andSERVERSSL_HANDSHAKEfrom server side. In this case, we should have both client and server sides decrypted, even though we never had access to back-end server: Notice added anhttpfilter to show you both client and and server traffic were decrypted this time. tcpdump --f5 ssl option This was introduced in 15.x and we don't need to change virtual server configuration by adding iRules. The only thing we need to do is to enabletcpdump.sslproviderdb variable which is disabled by default: After that, when we take tcpdump capture, we just need to add --f5 ssl to the command like this: Notice that we've got a warning message because Master Secret will be copied to tcpdump capture itself, so we need to be careful with who we share such capture with. I had to update my Wireshark to v3.2.+ and clicked onAnalyze→Enabled Protocols: And enable F5 TLS dissector: Once we open the capture, we can find all the information you need to create our PMS file embedded in the capture: Very cool, isn't it? We can then copy the Master Secretand Client Random values by right clicking like this: And then paste it to a blank PMS file. I first pasted the Client Random value followed by Master Secret value like this: Note: I manually typedCLIENT_RANDOMand then pasted both values for both client and server sides directly from tcpdump capture. The last step was to go toWireshark→Preferences→Protocols→TLSand add it toPre-master-Secret log filenameand clickOK: Fair enough! Capture decrypted on both client and server sides: I usedhttpfilter to display only decrypted HTTP packets just like in iRule section. Appendix 1 How do we know which Key Exchange method is being used? RSA private key can only decrypt traffic on Wireshark if RSA is the key exchange method negotiated during TLS handshake. Client side will tell the Server side which ciphers it support and server side will reply with the chosen cipher onServer Hellomessage. With that in mind, on Wireshark, we'd click onServer Helloheader underCipher Suite: Key Exchange and Authentication both come before theWITHkeyword. In above example, because there's only RSA we can say that RSA is used for both Key Exchange and Authentication. In the following example, ECDHE is used for key exchange and RSAfor authentication: Appendix 2 Disabling Session Resumption and Prioritising RSA key exchange We can set Cache Size to 0 to disableTLS session resumptionand change the Cipher Suites to anything that makes BIG-IP pick RSA for Key Exchange:Client SSL Authentication on BIG-IP as in-depth as it can go
Quick Intro In this article, I'm going to explain how SSL client certificate authentication works on BIG-IP and explain what actually happens during client authentication as in-depth as I can, showing the TLS headers on Wireshark. This article is about the client side of BIG-IP (Client SL profile) authenticating a client connecting to BIG-IP. The Topology For reference so we can follow Wireshark output: How to Configure Client Certificate Authentication on Client SSL profile Essentially, what we're doing here is making BIG-IP verify client's credentials before allowing the TLS handshake to proceed. However, such credentials are in the form of a client certificate. The way to do this is to configure BIG-IP by: Adding a CA file to Trusted Certificate Authorities (ca-file in tmsh) to validate client certificate Optionally adding same CA that signed client certificate to Advertised Certificate Authorities Enforcing Client Certificate validation by setting Client Certificate option on BIG-IP to require Optionally setting the Frequency of such checks if we don't want to stick to the defaults. I'll go through each option now. Adding CA file to Trusted Certificate Authorities We should add to Trusted Certificate Authorities a single certificate file (*.crt) with one CA or concatenated file with 2 or more CAs with the purpose of validating client certificate, i.e. confirming client's identity. Upon receiving client certificate, BIG-IP will go through this list of CAs and confirm client's identity. It also has another purpose which is to authenticate BIG-IP to client but it's out of the scope of this article. Optionally add CA file to Advertised Certificate Authorities Trusted Certificate Authoritiesexplicitly tells BIG-IP the CA or chain of CAs it will use to validate client certificate whereasAdvertised Certificate Authorities tells client in advance what kind of CA BIG-IP trusts so that client can make the decision about which certificate to send to BIG-IP: Why would we use Advertised Certificate Authorities? Let's imagine a situation where Client's application has more than one Client Certificate configured. How is it going to figure out which certificate to send to BIG-IP? That's where Advertised Certificate Authorities comes to rescue us! When we add our CA bundle to Advertised Certificate Authorities, we're telling BIG-IP to add it to a header field named Distinguished Names within Certificate Request message. I dedicated the Appendix section to show you more in-depth how changing Advertised Certificate Authority affects Certificate Request header. Configuring BIG-IP to enforce Client Certificate validation To enable client certificate authentication on BIG-IP we change Local Traffic››Profiles : SSL : Client›› Client Certificate to request: The default is set to ignore where client certificate authentication is disabled. If we truly want to enable client certificate validation we need to select require. The reason why is because request makes BIG-IP request a client certificate from the client but BIG-IP will not perform the validation to confirm if the certificate sent is valid in this mode. The following subsections explain each option. Ignore Client Certificate Authentication is disabled (the default). BIG-IP never sends Certificate Request to client and therefore client does not need to send its certificate to BIG-IP. In this case, TLS handshake proceeds successfully without any client authentication: pcap:ssl-sample-peer-cert-mode-ignore.pcap Wireshark filter used:frame.number == 5 or frame.number == 6 Request BIG-IP requests Client Certificate by sending Certificate Request message but does not check whether client certificate is valid which is not really client authentication, is it? This means that ca-file(Trusted Certificate Authorities in the GUI) will not be used to validate client certificate and we will consider any certificate sent to us to be valid. For example, inssl-sample-peer-cert-mode-request-with-no-client-cert-sent.pcapwe now see that BIG-IP sends aCertificate Requestmessage and client responds with aCertificatemessage this time: Because I didn't add any client certificate to my browser, it sent a blank certificate to BIG-IP. Again, BIG-IP did not perform any validation whatsoever, so TLS handshake proceeded successfully. We can then conclude that this setting only makes BIG-IP request client certificate and that's it. Require It behaves just like Request but BIG-IP also performs client certificate validation, i.e. BIG-IP will use CA we hopefully added to ca-file (Trusted Certificate Authorities in the GUI) to confirm if client certificate is valid. This means that if we don't add a CA to Trusted Certificate Authorities (ca-file in tmsh) then validation will fail. Setting the Frequency of Client Certificate Requests This setting specifies the frequency BIG-IP authenticates client by enabling/disabling TLS session resumption. It has only 2 options: once BIG-IP requests client certificate during first handshake and no longer re-authenticates client as long as TLS session is reused and valid. The way BIG-IP does it is by using Session Resumption/Reuse. During first TLS handshake from client, BIG-IP sends a Session ID to Client within Server Hello header and in subsequent TLS connections, assuming session ID is still in BIG-IP's cache and client re-sends it back to BIG-IP, then session will be resumed every time client tries to establish a TLS session (respecting cache timeout). First time client sends Client Hello with blank session ID as it's cache is empty and then it is assigned a Session ID by BIG-IP (409f...): pcap:ssl-sample-clientcert-auth-once-enabled.pcap Wireshark filter used:filter:!ip.addr == 172.16.199.254 and frame.number > 1 and frame.number < 7 Certificate Requestconfirms BIG-IP is trying to authenticate client. Notice Session ID BIG-IP sent to client is 409f7... Then when Client tries to go through another TLS handshake and sends above session ID in Client Hello (packet #70 below). BIG-IP then confirms session is being resumed by sending samesession IDin Server Hello back to client: Wireshark filter used:!ip.addr == 172.16.199.254 and frame.number > 66 and frame.number < 73 This resumed TLS handshake just means we will not go through full handshake and will no longer need to exchange keys, select ciphers or re-authenticate client as we're reusing those already negotiated in the full TLS handshake where we first received Session ID 409f... always BIG-IP requests client certificate, i.e. re-authenticates client at every handshake. On BIG-IP, this is accomplished by disabling session reuse which makes BIG-IP not to sendSession IDback to Client in the beginning and forcing a full TLS handshake every time. pcap:ssl-sample-clientcert-auth-always-enabled.pcap Wireshark filter used: !ip.addr == 172.16.199.254 and ((frame.number > 1 and frame.number < 7) or (frame.number > 74 and frame.number < 80)) Appendix: Understanding how Advertised Certificate Authority field affects Certificate Request header For this test, I've got the following: myCAbundle.crt: concatenation of root_ca.crt and ltm2.crt (signed by root_ca.crt) client_cert.crt: added to Firefox and signed by ltm2.crt I've also added myCAbundle.crt to Trusted Certificate Authorities so BIG-IP is able to verify that client_cert.crt is valid. For each test, I will use change Advertised Certificate Authorities so we can see what happens. We'll go through 3 tests here: Setting Advertised Certificate Authority to None Setting Advertised Certificate Authority to a certificate that didn't sign client cert Setting Advertised Certificate Authority to a bundle that signed client cert Setting Advertised Certificate Authority to None Note that even though no CA was advertised in Certificate Request message, BIG-IP still advertises Certificate typesandSignature Hash Algorithmsso that client knows in advance what kind of certificate (RSA, DSS or ECDSA) and hash algorithms BIG-IP supports in advance. If client certificate had not been signed using any of the certificate types and hashing algorithms listed then handshake would have failed. However, in this case validation is successful as we can see on frame #8 that client certificate is RSA type and hashed with SHA1: pcap: ssl-sample-advcert-none.pcap filter used: !ip.addr == 172.16.199.254 and frame.number > 1 and frame.number < 16 It's worth noting that Distinguished Names is NOT populated and has length of zero because we didn't attach a bundle to Advertised Certificate Authorities. In this case, it worked fine because my client browser had only one certificate attached, so it shouldn't cause a problem anyway. Setting Advertised Certificate Authority to a certificate that didn't sign client cert pcap: ssl-sample-advcert-default-firefox.pcap Wireshark filter used: None I've set Advertised Certificate Authority to default.crt as this is NOT the CA that signed client's certificate: The difference here when compared to None is that now we can see that Distinguished Names is now populated with the certificate I added (default.crt): However, even though I added the correct certificate to my Firefox browser, it sent a blank certificate instead. Why? That's because BIG-IP signalled in Distinguished Names that default.crt is the CA that signed the certificate BIG-IP is looking for and as Firefox doesn't have any certificate signed by default.crt, it just sent a blank certificate back to BIG-IP. Also, because BIG-IP is now performing proper validation, i.e. comparing whatever client certificate is sent to it with the CA list added to Trusted Certificate Authorities, it knows a blank certificate is not valid and terminates the TLS handshake with a Fatal Alert. Setting Advertised Certificate Authority to a bundle that signed client cert pcap: ssl-sample-advcert-ltm2chainedwithrootca.pcap filter used: !ip.addr == 172.16.199.254 and frame.number > 1 Now I've set Advertised Certificate Authority to the correct bundle that signed my client certificate: And indeed handshake succeeds because: BIG-IP advertises myCAbundle.crt in Certificate Request >> Distinguished Names header, as per Advertised Certificate Authority configuration By reading Distinguished Names field, Client correctly sends the correct client certificate back to BIG-IP BIG-IP correctly validates client certificate using myCAbundle configured on Trusted Certificate Authorities Hope this article provides some clarification about these mysterious TLS headers.How Proxy SSL works on BIG-IP
1. Lab Scenario Lab test results: Client completes 3-way handshake with BIG-IP and BIG-IP immediately opens and completes 3-way handshake with back-end server Upon receiving Client Hello on client-side, BIG-IP immediately sends Client Hello on server-side as it is BIG-IP copies same cipher suite list seen on client-side Client Hello to server-side Client Hello BIG-IP ignores what is configured on both Client SSL or Server SSL profiles. As soon as BIG-IP receives Server Hello it confirms two things: Is RSA the chosen key exchange mechanism in Cipher Suite on Server Hello message sent from back-end server? Does Certificate sent by back-end matches the one configured on Server SSL profile on BIG-IP? ONLY if both conditions above match BIG-IP proceeds with handshake. Otherwise, BIG-IP sends a Handshake Failure (Fatal Alert) to both Server and Client with reset cause ofillegal_parameter BIG-IP copies same Server SSL/Back-end Server certificate to Certificate message sent to Client on client-side BIG-IP completely ignores certificate you configured on Client SSL. It always uses the same server-side certificate. Assuming TLS handshake completes successfully BIG-IP is able to decrypt all client-side as well as server-side data which is the whole purpose of Proxy SSL. 2. How Proxy SSL works When Proxy SSL is enabled,BIG-IP does its best to match client-side to server-side connection in terms of negotiation and traffic to make it as transparent as possible to both client and back-end server and at the same allowing BIG-IP to decrypt traffic. About data transparency BIG-IP achieves transparency by copying whatever client and server sends back and forth. About data decryption BIG-IP has an extra configuration requirement for Proxy SSL configuration (according toK13385) that you should add the same certificate/key present on the back-end server to Certificate/Key fields on Server SSL proxy of BIG-IP. This way BIG-IP can decrypt both client and server sides of connection. In practical terms and to achieve this, BIG-IP completely changes the original purpose of Server SSL Certificate and Key fields. Here's my config: Certificate/Key fields above are no longer used for the purpose described inK14806, i.e. to independently authenticate BIG-IP to back-end server through Client Authentication. Instead, when Proxy SSL is enabled it is used to validate if Certificate sent by back-end server is the same one in this field. If so, BIG-IP also copies this certificate to Certificate message sent to Client on client-side. Noticethat when Proxy SSL is NOT bypassedCertificate configured on Client SSL profile is never used. As soon as I sent first request to Wildcard forwarding VIP BIG-IP establishes TCP connection on client-side first and then immediately on server-side: The next step is to forward exactly the sameClient Hellowe receive from Client on client-side to Server on server-side: Now server sends Server Hello: The first thing BIG-IP checks is key exchange mechanism as Proxy SSL has to use RSA (frame 12): Now BIG-IP checks if Certificate insideCertificatemessage is the same as the one configured on Server SSL. In this case I have used Certificate's unique serial number to confirm this. On BIG-IP: Now on Server's message (frame 12): Now BIG-IP sends this same certificate inServer Hellomessage client-side and we can confirm from Serial number that it is the same: From this moment handshake should complete successfully and BIG-IP is maintaining 2 separate connections using the same certificate/key pair on client and server side with the ability to decrypt both. 3. Troubleshooting Proxy SSL when BIG-IP is the culprit Typically, if BIG-IP is the culprit it either because back-end server selected non-RSA key exchange cipher or because cert/key which are not supported. In another test I used DHE on purpose andBIG-IP resets connection immediately after Server Hello message is received from back-end server which is typical sign of validation error: I confirmed back-end server had selected ECDHE key exchange cipher which is not supported by Proxy SSL (frame 12): In case you don't know yet here's how you work out key exchange cipher: Disabling non-RSA cipher on back-end server did the trick to fix the above error as Proxy SSL only supports RSA key exchange. 4. Setting Up Proxy SSL on BIG-IP I used very minimal configuration for this lab and the only thing I did was to create a wildcard forwarding virtual server using Standard VIP: I enabled proxy-ssl on both Client and Server SSL profiles and added back-end server certificate (ltm3.crt) and key (ltm3.key) to Server SSL profile: I also disabled (EC)DHE and explicitly configured RSA as key exchange mechanism in my back-end server. I also confirmed back-end server was also usingltm3.crt/ltm3.keyas it must match the one configured on Server SSL profile: And it all worked fine:TLS Stateful vs Stateless Session Resumption
1. Preliminary Information TLS Session Resumption allows caching of TLS session information. There are 2 kinds: stateful and stateless. In stateful session resumption, BIG-IP stores TLS session information locally. In stateless session resumption, such job is delegated to the client. BIG-IP supports both stateful and stateless TLS session resumption. Enabling stateful or stateless session resumption is just a matter of ticking/unticking a tickbox on LTM's Client SSL profile: In this article, I'm going to walk through how session resumption works by performing a lab test. Here's my topology: Do not confuseSession Reuse/Resumption withRenegotiation. Renegotiation uses the same TCP connection to renegotiate security parameters which does not involved Session ID or Session Tickets. For more information please refer to SSL Legacy Renegotiation Secure Renegotiation. 2. How Stateful Session Resumption works Capture used:ssl-sample-session-ticket-disabled.pcap 2.1 New session Statefulmeans BIG-IP will keep storing session information from as many clients its cache allows and TLS handshake will proceed as follows: We can see above that Client sends an empty Session ID field and BIG-IP replies with a new Session ID (filter used:tcp.stream eq 0). After that, full handshake proceeds normally where Certificate and Client Key Exchange are sent and there is also the additional cost CPU-wise to compute the keys: 2.2 Reusing Previous Session Now both Client and Server have Session ID 56bcf9f6ea40ac1bbf05ff7fd209d423da9f96404103226c7f927ad7a2992433 stored in their TLS session cache. The good thing about it is that in the next TLS connection request, client won't need to go through the full TLS handshake again. Here's what we see: Client just sends Session ID (56bcf9f6ea40ac1bbf05ff7fd209d423da9f96404103226c7f927ad7a2992433) it previously learnt from BIG-IP (via Server Hello from previous connection) on its Client Hello message. BIG-IP then confirms this session ID is in its SSL Session cache and they both go through what is known as abbreviated TLS handshake. No certificate or key information is exchanged during abbreviated TLS handshake and previously negotiated keys are re-used. 3. How Stateless Session Resumption works Capture used:ssl-sample-session-ticket-enabled-2.pcap 3.1 New Session Because of the burden on BIG-IP that has to store one session per client,RFC5077suggested a new way of doing session Resumption that offloads the burden of keeping all TLS session information to client and nothing else needs to be stored on BIG-IP. Let's see the magic! Client first signals it supports stateless session resumption by adding SessionTickets TLS extension to its Client Hello message (in green): BIG-IP also signals back to client (in red) it supports SessionTicket TLS by adding empty SessionTicket TLS extension.Notice thatSession IDis NOT used here! The TLS handshake proceeds normally just like in stateful session resumption. However, just before handshake is completed (with Finished message), BIG-IP sends a new TLS message calledNew Session Ticketwhich consists of encrypted session information (e.g. master secret, cipher used, etc) where BIG-IP is able to decrypt later using a unique key it generates only for this purpose: From this point on, client (10.199.3.135) keeps session ticket in its TLS cache until next time it needs to connect to the same server (assuming session ticket did not expire). 3.2 Reusing Previous Session Now, when the same client wants to re-use previous session,it forwards the same session ticket aboveinSessionTicket TLS extensionon its Client Hello message as seen below: As we've noticed, Client also creates a new Session ID used for the following purpose: Server replies back with same session ID: BIG-IP accepted Session Ticket and is going to reuse the session. Server replies with empty/different Session ID: BIG-IP decided to go through full handshake either because Session Ticket expired or it is falling back to stateful session resumption. PS: Such session ID is NOT stored on BIG-IP otherwise it would defeat the purpose of stateless session reuse. It is a one-off usage just to confirm to client BIG-IP accepted session ticket they sent and we're not going to generate new session keys. In our example, BIG-IP successfully accepted and reused TLS session. We can confirm that an abbreviated TLS handshake took place and on Server Hello message BIG-IP replied back with same session ID client sent (to BIG-IP): Now, client This is session resumption in action and BIG-IP doesn't even have to store session information locally, making it a more scalable option when compared to stateful session resumption.JA4 Part 2: Detecting and Mitigating Based on Dynamic JA4 Reputation
In my previous article on JA4 I provided a brief introduction to what is JA4 and JA4+, and I shared an iRule that enables you to generate a JA4 client TLS fingerprint. But having a JA4 fingerprint (or any "identifier") is only valuable if you can take some action on it. It is even more valuable when you can take immediate action on it. In this article, I'll explain how I integrated F5 BIG-IP Advanced WAF with a third-party solution that allowed me to identify JA4s that were consistently doing "bad" things, build a list of those JA4s that have a "bad" reputation, pull that list into the F5 BIG-IP, and finally, make F5 Advanced WAF blocking decisions based on that reputation. Understanding JA4 Fingerprints It is important to understand that a JA4 TLS fingerprint, or any TLS fingerprint for that matter, is NOT a fingerprint of an individual instance of a device or browser. Rather, it is a fingerprint of a TLS "stack" or application. For example, all Chrome browsers of the same version and the same operating system will generate the same JA4 fingerprint*. Similarly, all Go HTTP clients with the same version and operating system will generate an identical JA4 fingerprint. Because of this, we have to be careful when taking action based on JA4 fingerprints. We cannot simply block in our various security devices based on JA4 fingerprint alone UNLESS we can be certain that ALL (or nearly all) requests with that JA4 are malicious. To make this determination, we need to watch requests over time. TLDR; I used CrowdSec Security Engine to build a JA4 real-time reputation database; and 3 irules, an iCall script, and a custom WAF violation to integrate that JA4 reputation into F5 BIG-IP Advanced WAF. CrowdSec and John Althouse - Serendipity While at Black Hat each year, I frequently browse the showroom floor (when I'm not working the F5 booth) looking for cool new technology, particularly cool new technology that can potentially be integrated with F5 security solutions. Last year I was browsing the floor and came across CrowdSec. As the name suggests, CrowdSec provides a crowd-sourced IP reputation service. I know, I know. On the surface this doesn't sound that exciting — there are hundreds of IP reputation services out there AND IP address, as an identifier of a malicious entity, is becoming (has become?) less and less valuable. So what makes CrowdSec any different? Two things jumped out at me as I looked at their solution. First, while they do provide a central crowd-sourced IP reputation service like everyone else, they also have "Security Engines". A security engine is an agent/application that you can install on-premises that can consume logs from your various security devices, process those logs based on "scenarios" that you define, and produce a reputation database based on those scenarios. This enables you to create an IP reputation feed that is based on your own traffic/logs and based on your own conditions and criteria for what constitutes "malicious" for your organization. I refer to this as "organizationally-significant" reputation. AND, because this list can be updated very frequently (every few seconds if you wanted) and pushed/pulled into your various security devices very frequently (again, within seconds), you are afforded the ability to block for much shorter periods of time and, possibly, more liberally. Inherent in such an architecture, as well, is the ability for your various security tools to share intelligence in near real-time. i.e. If your firewall identifies a bad actor, your WAF can know about that too. Within seconds! At this point you're probably wondering, "How does this have anything to do with JA4?" Second, while the CrowdSec architecture was built to provide IP reputation feeds, I discovered that it can actually create a reputation feed based on ANY "identifier". In the weeks leading up to Black Hat last year, I had been working with John Althouse on the JA4+ spec and was actually meeting him in person for the first time while there. So JA4 was at the forefront of my mind. I wondered if I could use CrowdSec to generate a reputation based on a JA4 fingerprint. Yes! You can! Deploying CrowdSec As soon as I got home from Black Hat, I started playing. I already had my BIG-IP deployed, generating JA4s, and including those in the WAF logs. Following the very good documentation on their site, I created an account on CrowdSec's site and deployed a CrowdSec Security Engine on an Ubuntu box that I deployed next to my BIG-IP. It is beyond the scope of this article to detail the complete deployment process but, I will include details relevant to this article. After getting the CrowdSec Security Engine deployed I needed to configure a parser so that the CrowdSec Security Engine (hereafter referred to simply as "SE") could properly parse the WAF logs from F5. Following their documentation, I created a YAML file at /etc/crowdsec/parsers/s01-parse/f5-waf-logs.yaml: onsuccess: next_stage debug: false filter: "evt.Parsed.program == 'ASM'" name: f5/waf-logs description: "Parse F5 ASM/AWAF logs" pattern_syntax: F5WAF: 'unit_hostname="%{DATA:unit_hostname}",management_ip_address="%{DATA:management_ip_address}",management_ip_address_2="%{DATA:management_ip_address_2}",http_class_name="%{DATA:http_class_name}",web_application_name="%{DATA:web_application_name}",policy_name="%{DATA:policy_name}",policy_apply_date="%{DATA:policy_apply_date}",violations="%{DATA:violations}",support_id="%{DATA:support_id}",request_status="%{DATA:request_status}",response_code="%{DATA:response_code}",ip_client="%{IP:ip_client}",route_domain="%{DATA:route_domain}",method="%{DATA:method}",protocol="%{DATA:protocol}",query_string="%{DATA:query_string}",x_forwarded_for_header_value="%{DATA:x_forwarded_for_header_value}",sig_ids="%{DATA:sig_ids}",sig_names="%{DATA:sig_names}",date_time="%{DATA:date_time}",severity="%{DATA:severity}",attack_type="%{DATA:attack_type}",geo_location="%{DATA:geo_location}",ip_address_intelligence="%{DATA:ip_address_intelligence}",username="%{DATA:username}",session_id="%{DATA:session_id}",src_port="%{DATA:src_port}",dest_port="%{DATA:dest_port}",dest_ip="%{DATA:dest_ip}",sub_violations="%{DATA:sub_violations}",virus_name="%{DATA:virus_name}",violation_rating="%{DATA:violation_rating}",websocket_direction="%{DATA:websocket_direction}",websocket_message_type="%{DATA:websocket_message_type}",device_id="%{DATA:device_id}",staged_sig_ids="%{DATA:staged_sig_ids}",staged_sig_names="%{DATA:staged_sig_names}",threat_campaign_names="%{DATA:threat_campaign_names}",staged_threat_campaign_names="%{DATA:staged_threat_campaign_names}",blocking_exception_reason="%{DATA:blocking_exception_reason}",captcha_result="%{DATA:captcha_result}",microservice="%{DATA:microservice}",tap_event_id="%{DATA:tap_event_id}",tap_vid="%{DATA:tap_vid}",vs_name="%{DATA:vs_name}",sig_cves="%{DATA:sig_cves}",staged_sig_cves="%{DATA:staged_sig_cves}",uri="%{DATA:uri}",fragment="%{DATA:fragment}",request="%{DATA:request}",response="%{DATA:response}"' nodes: - grok: name: "F5WAF" apply_on: message statics: - meta: log_type value: f5waf - meta: user expression: "evt.Parsed.username" - meta: source_ip expression: "evt.Parsed.ip_client" - meta:violation_rating expression:"evt.Parsed.violation_rating" - meta:request_status expression:"evt.Parsed.request_status" - meta:attack_type expression:"evt.Parsed.attack_type" - meta:support_id expression:"evt.Parsed.support_id" - meta:violations expression:"evt.Parsed.violations" - meta:sub_violations expression:"evt.Parsed.sub_violations" - meta:session_id expression:"evt.Parsed.session_id" - meta:sig_ids expression:"evt.Parsed.sig_ids" - meta:sig_names expression:"evt.Parsed.sig_names" - meta:method expression:"evt.Parsed.method" - meta:device_id expression:"evt.Parsed.device_id" - meta:uri expression:"evt.Parsed.uri" nodes: - grok: pattern: '%{GREEDYDATA}X-JA4: %{DATA:ja4_fp}\\r\\n%{GREEDYDATA}' apply_on: request statics: - meta: ja4_fp expression:"evt.Parsed.ja4_fp" Sending WAF Logs On the F5 BIG-IP, I created a logging profile to send the WAF logs to the CrowdSec Security Engine IP address and port. Defining "Scenarios" At this point, I had the WAF logs being sent to the SE and properly being parsed. Now I needed to define the "scenarios" or the conditions under which I wanted to trigger and alert for an IP address or, in this case, a JA4 fingerprint. For testing purposes, I initially created a very simple scenario that flagged a JA4 as malicious as soon as I saw 5 violations in a sliding 30 second window but only if the violation rating was 3 or higher. That worked great! But that would never be practical in the real world (see the Understanding JA4 Fingerprints section above). I created a more practical "scenario" that only flags a JA4 as malicious if we have seen at least X number of requests AND more than 90% of requests from that JA4 have triggered some WAF violation. The premise with this scenario is that there should be enough legitimate traffic from popular browsers and other client types to keep the percentage of malicious traffic from any of those JA4s below 90%. Again, following the CrowdSec documentation, I created a YAML file at /etc/crowdsec/scenarios/f5-waf-ja4-viol-percent.yaml: type: conditional name: f5/waf-ja4-viol-percent description: "Raise an alert if the percentage of requests from a ja4 finerprint is above X percent" filter: "evt.Meta.violations != 'JA4 Fingerprint Reputation'" blackhole: 300s leakspeed: 5m capacity: -1 condition: | len(queue.Queue) > 10 and (count(queue.Queue, Atof(#.Meta.violation_rating) > 1) / len(queue.Queue)) > 0.9 groupby: "evt.Meta.ja4_fp" scope: type: ja4_fp expression: evt.Meta.ja4_fp labels: service: f5_waf type: waf_ja4 remediation: true debug: false There are a few key lines to call out from this configuration file. leakspeed: This is the "sliding window" within which we are looking for our "scenarios". i.e. events "leak" out of the bucket after 5 minutes. condition: The conditions under which I want to trigger this bucket. For my scenario, I have defined a condition of at least 10 events (with in that 5 minute window) AND where the total number of events, divided by the number of events where the violation rating is above 1, is greater than 0.9. in other words, if more than 90% of the requests have triggered a WAF violation with a rating higher than 1. filter: used to filter out events that you don't want to include in this scenario. In my case, I do not want to include requests where the only violation is the "JA4 Fingerprint Reputation" violation. groupby: this defines how I want to group requests. Typiiccally, in most CrowdSec scenarios this wil be some IP address field from the logs. In my scenario, I wanted to group by the JA4 fingerprint parsed out of the WAF logs. blackhole: this defines how long I want to "silence" alerts per JA4 fingerprint after this scenario has triggered. This prevents the same scenario from triggering repeatedly every time a new request comes into the bucket. scope: the scope is used by the reputation service to "categorize" alerts triggered by scenarios. the type field is used to define the type of data that is being reported. In most CrowdSec scenarios the type is "ip". In my case, I defined a custom type of "ja4_fp" with an "expression" (or value) of the JA4 fingerprint extracted from the WAF logs. Defining "Profiles" In the CrowdSec configuration "profiles" are used to define the remediation that should be taken when a scenario is triggered. I edited the /etc/crowdsec/profiles.yaml file to include the new profile for my JA4 scenario. name: ban_ja4_fp filters: - Alert.Remediation == true && Alert.GetScope() == "ja4_fp" decisions: - type: ban scope: "ja4_fp" duration: 5m debug: true on_success: continue --- ##### Everything below this point was already in the profiles.yaml file. Truncated here for brevity. name: default_ip_remediation #debug: true filters: - Alert.Remediation == true && Alert.GetScope() == "Ip" decisions: ... on_success: break Again, there are a few key lines from this configuration file. First, I only added a new profile named "ban_ja4_fp" with lines 1 through 9 in the file above. filters: Used to define which triggered scenarios should be included in this profile. In my case, all scenarios with the "remediation" label AND the "ja4_fp" scope. decisions: Used to define what type of remediation should be taken, for which "scope", and for how long. In my case, I chose the default of "ban", for the "ja4_fp" scope, and for 5 minutes. With this configuration in place I sent several malicious requests from my browser to my test application protected by the F5 Advanced WAF. I then checked the CrowdSec decisions list and voila! I had my browser's JA4 fingerprint listed! This was great but I wanted to be able to take action based on this intelligence in the F5 WAF. CrowdSec has the concept of "bouncers". Bouncers are devices the can take action on the remediation decisions generated by the SEs. Technically, anything that can call the local CrowdSec API and take some remediating action can be a bouncer. So, using the CLI on the CrowdSec SE, I defined a new "bouncer" for the F5 BIG-IP. ubuntu@xxxxxxxx:~$ sudo cscli bouncer add f5-bigip Api key for 'f5-bigip': xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx Please keep this key since you will not be able to retrieve it! I knew that I could write an iRule that could call the SE API. However, the latency introduced by a sideband API call on EVERY HTTP request would just be completely untenable. I wanted a way to download the entire reputation list at a regular interval and store it on the F5 BIG-IP in a way that would be easily and efficiently accessible from the data plane. This sounded like a perfect job for an iCall script. Customizing the F5 BIG-IP Configuration If you are not familiar with iCall scripts, they are a programmatic way of checking or altering the F5 configuration based on some trigger; they are to the F5 BIG-IP management plane what iRules are to the data plane. The trigger can be some event, condition, log message, time interval, etc. I needed my iCall script to do two things. First, pull the reputation list from the CrowdSec SE. Second, store that list somewhere accessible to the F5 data plane. Like many of you, my first thought was either an iFile or a data group. Both of these are easily configurable components accessible via iCall scripts that are also accessible via iRules. For several reasons that I will not bother to detail here, I did not want to use either of these solutions, primarily for performance reasons (this reputation lookup needs to be very performant). And the most performant place to store information like this is the session table. The session table is accessible to iRules via "table" commands. However, the session table is not accessible via iCall scripts. At least not directly. I realized that I could send an HTTP request using the iCall script, AND that HTTP request could be to a local virtual server on the same BIG-IP where I could use an iRule to populate the session table with the JA4 reputation list pulled from the CrowdSec SE. The iCall Script From the F5 BIG-IP CLI I created the following iCall script using the tmsh command 'tmsh create sys icall script crowdsec_ja4_rep_update': sys icall script crowdsec_ja4_rep_update { app-service none definition { package require http set csapi_resp [http::geturl http://10.0.2.240:8080/v1/decisions/stream?startup=true&scopes=ja4_fp -headers "X-api-Key 1a234xxxxxxxxxxxxxxe56fab7"] #tmsh::log "[http::data ${csapi_resp}]" set payload [http::data ${csapi_resp}] http::cleanup ${csapi_resp} set tupdate_resp [http::geturl http://10.0.1.110/updatetables -type "application/json" -query ${payload}] tmsh::log "[http::data ${tupdate_resp}]" http::cleanup ${tupdate_resp} } description none events none } Let's dig through this iCall script line by line: 4. Used to "require" or "include" the TCL http library. 5. HTTP request to the CrowdSec API to get the JA4 reputation list. 10.0.2.240:8080 is the IP:port of the CrowdSec SE API /v1/decisions/stream is the API endpoint used to grab an entire reputation list (rather than just query for the status of an individual IP/JA4) startup=true tells the API to send the entire list, not just additions/deletions since the last API call scopes=ja4_fp limits the returned results to just JA4 fingerprint-type decisions -headers "X-api-Key xxxxxxxxxxxxxxxxxxxxxxxxxx" includes the API key generated previously to authenticate the F5 BIG-IP as a "bouncer" 7. Store just the body of the API response in a variable called "payload" 8. free up memory used by the HTTP request tot eh CrowdSec API 9. HTTP Request to a local virtual server (on the same F5 BIG-IP) including the contents of the "payload" variable as the POST body. The IP address needs to be the IP address of the virtual server defined in the next step. An iRule will be created and placed on this virtual server that parses the "payload" and inserts the JA4 reputation list into the session table. An iCall script will not run unless an iCall handler is created that defines when that iCall script should run. I call handlers can be "triggered", "perpetual", or "periodic". I created the following periodic iCall handler to run this iCall script at regular intervals. sys icall handler periodic crowdsec-api-ja4 { interval 30 script crowdsec_ja4_list } This iCall handler is very simple; it has an "interval" for how often you want to run the script and the script that you want to run. I chose to run the iCall script every 30 seconds so that the BIGIP session table would be updated with any new malicious JA4 fingerprints very quickly. But you could choose to run the iCall script every 1 minute, 5 minutes, etc. The Table Updater Virtual Server and iRule I then created a HTTP virtual server with no pool associated to it. This virtual server exists solely to accept and process the HTTP requests from the iCall script. I then created the following iRule to process the requests and payload from the iCall script: proc duration2seconds {durstr} { set h 0 set m 0 set s 0 regexp {(\d+)h} ${durstr} junk h regexp {(\d+)m} ${durstr} junk m regexp {(\d+)\.} ${durstr} junk s set seconds [expr "(${h}*3600) + (${m}*60) + ${s}"] return $seconds } when HTTP_REQUEST { if { ([HTTP::uri] eq "/updatetables" || [HTTP::uri] eq "/lookuptables") && [HTTP::method] eq "POST"} { HTTP::collect [HTTP::header value "content-length"] } else { HTTP::respond 404 } } when HTTP_REQUEST_DATA { #log local0. "PAYLOAD: '[HTTP::payload]'" regexp {"deleted":\[([^\]]+)\]} [HTTP::payload] junk cs_deletes regexp {"new":\[([^\]]+)\]} [HTTP::payload] junk cs_adds if { ![info exists cs_adds] } { HTTP::respond 200 content "NO NEW ENTRIES" return } log local0. "CS Additions: '${cs_adds}'" set records [regexp -all -inline -- {\{([^\}]+)\},?} ${cs_adds}] set update_list [list] foreach {junk record} $records { set urec "" foreach k {scope value type scenario duration} { set v "" regexp -- "\"${k}\":\"?(\[^\",\]+)\"?,?" ${record} junk v log local0. "'${k}': '${v}'" if { ${k} eq "duration" } { set v [call duration2seconds ${v}] } append urec "${v}:" } set urec [string trimright ${urec} ":"] #log local0. "$urec" lappend update_list ${urec} } set response "" foreach entry $update_list { scan $entry {%[^:]:%[^:]:%[^:]:%[^:]:%s} scope entity type scenario duration if { [HTTP::uri] eq "/updatetables" } { table set "${scope}:${entity}" "${type}:${scenario}" indefinite $duration append response "ADDED ${scope}:${entity} FOR ${duration} -- " } elseif { [HTTP::uri] eq "/lookuptables" } { set remaining "" set action "" if { [set action [table lookup ${scope}:${entity}]] ne "" } { set remaining [table lifetime -remaining ${scope}:${entity}] append response "${scope}:${entity} - ${action} - ${remaining}s remaining\r\n" } else { append response "${scope}:${entity} - NOT IN TABLE\r\n" } } } HTTP::respond 200 content "${response}" } I have attempted to include sufficient inline comments so that the iRule is self-explanatory. If you have any questions or comments on this iRule please feel free to DM me. It is important to note here that the iRule is storing not only each JA4 fingerprint in the session table as a key but also the metadata passed back from the CrowdSec API about each JA4 reputation as the value for each key. This metadata includes the scenario name, the "type" or action, and the duration. So at this point I had a JA4 reputation list, updated continuously based on the WAF violation logs and CrowdSec scenarios. I also had an iCall script on the F5 BIG-IP that was pulling that reputation list via the local CrowdSec API every 30 seconds and pushing that reputation list into the local session table on the BIG-IP. Now I just needed to take some action based on that reputation list. Integrating JA4 Reputation into F5 WAF To integrate the JA4 reputation into the F5 Advanced WAF we only need two things: a custom violation defined in the WAF an iRule to lookup the JA4 in the local session table and raise that violation Creating a Custom Violation Creating a custom violation in F5 Advanced WAF (or ASM) will vary slightly depending on which version of the TMOS software you are running. In version 17.1 it is at Security ›› Options : Application Security : Advanced Configuration : Violations List. Select the User-Defined Violations tab and click Create. Give the Violation a Title and define the Type, Severity, and Attack Type. Finally, I modified the Learning and Blocking Settings of my policy to ensure that the new custom violation was set to Alarm and Block. F5 iRule for Custom Violation I then created the following iRule to raise this new custom WAF violation if the JA4 fingerprint is found in the reputation list in the local session table. when ASM_REQUEST_DONE { # Grab JA4 fingerprint from x-ja4 header # This header is inserted by the JA4 irule set ja4_fp [HTTP::header value "x-ja4"] # Lookup JA4 fingerprint in session table if { [set result [table lookup "ja4_fp:${ja4_fp}"]] ne "" } { # JA4 was found in session table, scan the value to get "category" and "action" scan ${result} {%[^:]:%s} action category # Initialize all the nested list of lists format required for the # violation details of the ASM::raise command set viol [] set viol_det1 [] set viol_det2 [] set viol_det3 [] # Populate the variables with values parsed from the session table for this JA4 lappend viol_det1 "JA4 FP" "${ja4_fp}" lappend viol_det2 "CrowdSec Category" "${category}" lappend viol_det3 "CrowdSec Action" "${action}" lappend viol ${viol_det1} ${viol_det2} ${viol_det3} # Raise custom ASM violation with violation details ASM::raise VIOL_JA4_REPUTATION ${viol} } } Again, I tried to include enough inline documentation for the iRule to be self-explanatory. Seeing It All In Action With everything in place, I sent several requests, most malicious and some benign, to the application protected by the F5 Advanced WAF. Initially, only the malicious requests were blocked. After about 60 seconds, ALL of the requests were being blocked due to the new custom violation based on JA4 reputation. Below is a screenshot from one of my honeypot WAF instances blocking real "in-the-wild" traffic based on JA4 reputation. Note that the WAF violation includes (1) the JA4 fingerprint, (2) the "category" (or scenario), and (3) the "action" (or type). Things to Note The API communication between the F5 BIG-IP and the CrowdSec SE is over HTTP. This is obviously insecure; for this proof-of-concept deployment I was just too lazy to spend the extra time to get signed certs on all the devices involved and alter the iCall script to use the TCL SSL library.SSL Orchestrator Advanced Use Cases: Reducing Complexity with Internal Layered Architecture
Introduction Sir Isaac Newton said, "Truth is ever to be found in the simplicity, and not in the multiplicity and confusion of things". The world we live in is...complex. No getting around that. But at the very least, we should strive for simplicity where we can achieve it. As IT folk, we often find ourselves mired in the complexity of things until we lose sight of the big picture, the goal. How many times have you created an additional route table entry, or firewall exception, or virtual server, because the alternative meant having a deeper understanding of the existing (complex) architecture? Sure, sometimes it's unavoidable, but this article describes at least one way that you can achieve simplicity in your architecture. SSL Orchestrator sits as an inline point of presence in the network to decrypt, re-encrypt, and dynamically orchestrate that traffic to the security stack. You need rules to govern how to handle specific types of traffic, so you create security policy rules in the SSL Orchestrator configuration to describe and take action on these traffic patterns. It's definitely easy to create a multitude of traffic rules to match discrete conditions, but if you step back and look at the big picture, you may notice that the different traffic patterns basically all perform the same core actions. They allow or deny traffic, intercept or bypass TLS (decrypt/not-decrypt), and send to one or a few service chains. If you were to write down all of the combinations of these actions, you'd very likely discover a small subset of discrete "functions". As usual, F5 BIG-IP and SSL Orchestrator provide some innovative and unique ways to optimize this. And so in this article we will explore SSL Orchestrator topologies "as functions" to reduce complexity. Specifically, you can reduce the complexity of security policy rules, and in doing so, quite likely increase the performance of your SSL Orchestrator architecture. SSL Orchestrator Use Case: Reducing Complexity with Internal Layered Architectures The idea is simple. Instead of a single topology with a multitude of complex traffic pattern matching rules, create small atomic topologies as static functions and steer traffic to the topologies by virtue of "layered" traffic pattern matching. Granted, if your SSL Orchestrator configuration is already pretty simple, then please keep doing what you're doing. You've got this, Tiger. But if your environment is getting complex, and you're not quite convinced yet that topologies as functions is a good idea, here are a few additional benefits you'll get from this topology layering: Dynamic egress selection: topologies as functions can define different egress paths. Dynamic CA selection: topologies as functions can use different local issuing CAs for different traffic flows. Dynamic traffic bypass: certain types of traffic can be challenging to handle internally. For example, mutual TLS traffic can be bypassed globally with the "Bypass on client cert failure" option in the SSL configuration, but bypassing mutual TLS sites by hostname is more complex. A layered architecture can steer traffic (by SNI) through a bypass topology, with a service chain. More flexible pattern recognition: for all of its flexibility, SSL Orchestrator security policy rules cannot catch every possible use case. External traffic pattern recognition, via iRules or CPM (LTM policies) offer near infinite pattern matching options. You could, for example, steer traffic based on incoming tenant VLAN or route domain for multi-tenancy configurations. More flexible automation strategies: as iRules, data groups, and CPM policies are fully automate-able across many AnO platforms (ex. AS3, Ansible, Terraform, etc.), it becomes exceedingly easy to automate SSL Orchestrator traffic processing, and removes the need to manage individual topology security policy rules. Hopefully these benefits give you a pretty clear indication of the value in this architecture strategy. So without further ado, let's get started. Configuration Before we begin, I'd like to make note of the following caveats: While every effort has been made to simplify the layered architecture, there is still a small element of complexity. If you are at all averse to creating virtual servers or modifying iRules, then maybe this isn't for you. But as you are reading this in a forum dedicated to programmability, I'm guessing you the reader are ready for a challenge. This is a "field contributed" solution, so not officially supported by F5. This topology layering architecture is applicable to all modern versions of SSL Orchestrator, from 5.0 to 8.0. While topology layering can be used for inbound topologies, it is most appropriate for outbound. The configuration below also only describes the layer 3 implementation. But layer 2 layering is also possible. With this said, there are just a few core concepts to understand: Basic layered architecture configuration - how the pieces fit together The iRules - how traffic moves through the architecture Or the CPM policies - an alternative to iRules Note again that this is primarily useful in outbound topologies. Inbound topologies are typically more atomic on their own already. I will cover both transparent and explicit forward proxy configurations below. Basic layered architecture configuration A layered architecture takes advantage of a powerful feature of the BIG-IP called "VIP targeting". The idea is that one virtual server calls another with negligible latency between the two VIPs. The "external" virtual server is client-facing. The SSL Orchestrator topology virtual servers are thus "internal". Traffic enters the external VIP and traffic rules pass control to any of a number of internal "topology function" VIPs. You certainly don't have to use the iRule implementation presented here. You just need a client-facing virtual server with an iRule that VIP-targets to one or more SSL Orchestrator topologies. Each outbound topology is represented by a virtual server that includes the application server name. You can see these if you navigate to Local Traffic -> Virtual Servers in the BIG-IP UI. So then the most basic topology layering architecture might just look like this: when CLIENT_ACCEPTED { virtual "/Common/sslo_my_topology.app/sslo_my_topology-in-t-4" } This iRule doesn't do anything interesting, except get traffic flowing across your layered architecture. To be truly useful you'll want to include conditions and evaluations to steer different types of traffic to different topologies (as functions). As the majority of security policy rules are meant to define TLS traffic patterns, the provided iRules match on TLS traffic and pass any non-TLS traffic to a default (intercept/inspection) topology. These iRules are intended to simplify topology switching by moving all of the complexity of traffic pattern matching to a library iRule. You should then only need to modify the "switching" iRule to use the functions in the library, which all return Boolean true or false results. Here are the simple steps to create your layered architecture: Step 1: Build a set of "dummy" VLANs. A topology must be bound to a VLAN. But since the topologies in this architecture won't be listening on client-facing VLANs, you will need to create a separate VLAN for each topology you intend to create. A dummy VLAN is a VLAN with no interface assigned. In the BIG-IP UI, under Network -> VLANs, click Create. Give your VLAN a name and click Finished. It will ask you to confirm since you're not attaching an interface. Repeat this step by creating unique VLAN names for each topology you are planning to use. Step 2: Build a set of static topologies as functions. You'll want to create a normal "intercept" topology and a separate "bypass" topology, though you can create as many as you need to encompass the unique topology functions. Your intercept topology is configured as such: L3 outbound topology configuration, normal topology settings, SSL configuration, services, service chains No security policy rules - just the ALL rule with TLS intercept action (and service chain), and optionally remove the built-in Pinners rule Attach to a dummy VLAN (a VLAN with no assigned interfaces) Your bypass topology should then look like this: L3 outbound topology configuration, skip the SSL Configuration settings, optionally re-use services and service chains No security policy rules - just the ALL rule with TLS bypass action (and service chain) Attach to a separate dummy VLAN (a VLAN with no assigned interfaces) Note the name you use for each topology, as this will be called explicitly in the iRule. For example, if you name the topology "myTopology", that's the name you will use in each "call SSLOLIB::target" function (more on this in a moment) . If you look in the SSL Orchestrator UI, you will see that it prepends "sslo_" (ex. sslo_myTopology). Don't include the "sslo_" portion in the iRule. Step 3: Import the SSLOLIB iRule (attached here). Name it "SSLOLIB". This is the library rule, so no modifications are needed. The functions within (as described below) will return a true or false, so you can mix these together in your switching rule as needed. Step 4: Import the traffic switching iRule (attached here). You will modify this iRule as required, but the SSLOLIB library rule makes this very simple. Step 5: Create your external layered virtual server. This is the client-facing virtual server that will catch the user traffic and pass control to one of the internal SSL Orchestrator topology listeners. Type: Standard Source: 0.0.0.0/0 Destination: 0.0.0.0/0 Service Port: 0 Protocol: TCP VLAN: client-facing VLAN Address Translation: disabled Port Translation: disabled Default Persistence Profile: ssl iRule: the traffic switching iRule Note that the ssl persistence profile is enabled here to allow the iRules to handle client side SSL traffic without SSL profiles attached. Also make sure that Address and Port Translation are disabled before clicking Finished. Step 6: Modify the traffic switching iRule to meet your traffic matching requirements (see below). You have the basic layered architecture created. The only remaining step is to modify the traffic switching iRule as required, and that's pretty easy too. The iRules I'll repeat, there are near infinite options here. At the very least you need to VIP target from the external layered VIP to at least one of the SSL Orchestrator topology VIPs. The iRules provided here have been cultivated to make traffic selection and steering as easy as possible by pushing all of the pattern functions to a library iRule (SSLOLIB). The idea is that you will call a library function for a specific traffic pattern and if true, call a separate library function to steer that flow to the desired topology. All of the build instructions are contained inside the SSLOLIB iRule, with examples. SSLOLIB iRule: https://github.com/f5devcentral/sslo-script-tools/blob/main/internal-layered-architecture/transparent-proxy/SSLOLIB Switching iRule: https://github.com/f5devcentral/sslo-script-tools/blob/main/internal-layered-architecture/transparent-proxy/sslo-layering-rule The function to steer to a topology (SSLOLIB::target) has three parameters: <topology name>: this is the name of the desired topology. Use the basic topology name as defined in the SSL Orchestrator configuration (ex. "intercept"). ${sni}: this is static and should be left alone. It's used to convey the SNI information for logging. <message>: this is a message to send to the logs. In the examples, the message indicates the pattern matched (ex. "SRCIP"). Note, include an optional 'return' statement at the end to cancel any further matching. Without the 'return', the iRule will continue to process matches and settle on the value from the last evaluation. Example (sending to a topology named "bypass"): call SSLOLIB::target "bypass" ${sni} "DSTIP" ; return There are separate traffic matching functions for each pattern: SRCIP IP:<ip/subnet> SRCIP DG:<data group name> (address-type data group) SRCPORT PORT:<port/port-range> SRCPORT DG:<data group name> (integer-type data group) DSTIP IP:<ip/subnet> DSTIP DG:<data group name> (address-type data group) DSTPORT PORT:<port/port-range> DSTPORT DG:<data group name> (integer-type data group) SNI URL:<static url> SNI URLGLOB:<glob match url> (ends_with match) SNI CAT:<category name or list of categories> SNI DG:<data group name> (string-type data group) SNI DGGLOB:<data group name> (ends_with match) Examples: # SOURCE IP if { [call SSLOLIB::SRCIP IP:10.1.0.0/16] } { call SSLOLIB::target "bypass" ${sni} "SRCIP" ; return } if { [call SSLOLIB::SRCIP DG:my-srcip-dg] } { call SSLOLIB::target "bypass" ${sni} "SRCIP" ; return } # SOURCE PORT if { [call SSLOLIB::SRCPORT PORT:5000] } { call SSLOLIB::target "bypass" ${sni} "SRCPORT" ; return } if { [call SSLOLIB::SRCPORT PORT:1000-60000] } { call SSLOLIB::target "bypass" ${sni} "SRCPORT" ; return } # DESTINATION IP if { [call SSLOLIB::DSTIP IP:93.184.216.34] } { call SSLOLIB::target "bypass" ${sni} "DSTIP" ; return } if { [call SSLOLIB::DSTIP DG:my-destip-dg] } { call SSLOLIB::target "bypass" ${sni} "DSTIP" ; return } # DESTINATION PORT if { [call SSLOLIB::DSTPORT PORT:443] } { call SSLOLIB::target "bypass" ${sni} "DSTPORT" ; return } if { [call SSLOLIB::DSTPORT PORT:443-9999] } { call SSLOLIB::target "bypass" ${sni} "DSTPORT" ; return } # SNI URL match if { [call SSLOLIB::SNI URL:www.example.com] } { call SSLOLIB::target "bypass" ${sni} "SNIURLGLOB" ; return } if { [call SSLOLIB::SNI URLGLOB:.example.com] } { call SSLOLIB::target "bypass" ${sni} "SNIURLGLOB" ; return } # SNI CATEGORY match if { [call SSLOLIB::SNI CAT:$static::URLCAT_list] } { call SSLOLIB::target "bypass" ${sni} "SNICAT" ; return } if { [call SSLOLIB::SNI CAT:/Common/Government] } { call SSLOLIB::target "bypass" ${sni} "SNICAT" ; return } # SNI URL DATAGROUP match if { [call SSLOLIB::SNI DG:my-sni-dg] } { call SSLOLIB::target "bypass" ${sni} "SNIDGGLOB" ; return } if { [call SSLOLIB::SNI DGGLOB:my-sniglob-dg] } { call SSLOLIB::target "bypass" ${sni} "SNIDGGLOB" ; return } To combine these, you can use simple AND|OR logic. Example: if { ( [call SSLOLIB::DSTIP DG:my-destip-dg] ) and ( [call SSLOLIB::SRCIP DG:my-srcip-dg] ) } Finally, adjust the static configuration variables in the traffic switching iRule RULE_INIT event: ## User-defined: Default topology if no rules match (the topology name as defined in SSLO) set static::default_topology "intercept" ## User-defined: DEBUG logging flag (1=on, 0=off) set static::SSLODEBUG 0 ## User-defined: URL category list (create as many lists as required) set static::URLCAT_list { /Common/Financial_Data_and_Services /Common/Health_and_Medicine } CPM policies LTM policies (CPM) can work here too, but with the caveat that LTM policies do not support URL category lookups. You'll probably want to either keep the Pinners rule in your intercept topologies, or convert the Pinners URL category to a data group. A "url-to-dg-convert.sh" Bash script can do that for you. url-to-dg-convert.sh: https://github.com/f5devcentral/sslo-script-tools/blob/main/misc-tools/url-to-dg-convert.sh As with iRules, infinite options exist. But again for simplicity here is a good CPM configuration. For this you'll still need a "helper" iRule, but this requires minimal one-time updates. when RULE_INIT { ## Default SSLO topology if no rules match. Enter the name of the topology here set static::SSLO_DEFAULT "intercept" ## Debug flag set static::SSLODEBUG 0 } when CLIENT_ACCEPTED { ## Set default topology (if no rules match) virtual "/Common/sslo_${static::SSLO_DEFAULT}.app/sslo_${static::SSLO_DEFAULT}-in-t-4" } when CLIENTSSL_CLIENTHELLO { if { ( [POLICY::names matched] ne "" ) and ( [info exists ACTION] ) and ( ${ACTION} ne "" ) } { if { $static::SSLODEBUG } { log -noname local0. "SSLO Switch Log :: [IP::client_addr]:[TCP::client_port] -> [IP::local_addr]:[TCP::local_port] :: [POLICY::rules matched [POLICY::names matched]] :: Sending to $ACTION" } virtual "/Common/sslo_${ACTION}.app/sslo_${ACTION}-in-t-4" } } The only thing you need to do here is update the static::SSLO_DEFAULT variable to indicate the name of the default topology, for any traffic that does not match a traffic rule. For the comparable set of CPM rules, navigate to Local Traffic -> Policies in the BIG-IP UI and create a new CPM policy. Set the strategy as "Execute First matching rule", and give each rule a useful name as the iRule can send this name in the logs. For source IP matches, use the "TCP address" condition at ssl client hello time. For source port matches, use the "TCP port" condition at ssl client hello time. For destination IP matches the "TCP address" condition at ssl client hello time. Click on the Options icon and select "Local" and "External". For destination port matches the "TCP port" condition at ssl client hello time. Click on the Options icon and select "Local" and "External". For SNI matches, use the "SSL Extension server name" condition at ssl client hello time. For each of the conditions, add a simple "Set variable" action as ssl client hello time. Name the variable "ACTION" and give it the name of the desired topology. Apply the helper iRule and CPM policy to the external traffic steering virtual server. The "first" matching rule strategy is applied here, and all rules trigger on ssl client hello, so you can drag them around and re-order as necessary. Note again that all of the above only evaluates TLS traffic. Any non-TLS traffic will flow through the "default" topology that you identify in the iRule. It is possible to re-configure the above to evaluate HTTP traffic, but honestly the only significant use case here might be to allow or drop traffic at the policy. Layered architecture for an explicit forward proxy You can use the same logic to support an explicit proxy configuration. The only difference will be that the frontend layered virtual server will perform the explicit proxy functions. The backend SSL Orchestrator topologies will continue to be in layer 3 outbound (transparent proxy) mode. Normally SSL Orchestrator would build this for you, but it's pretty easy and I'll show you how. You could technically configure all of the SSL Orchestrator topologies as explicit proxies, and configure the client facing virtual server as a layer 3 pass-through, but that adds unnecessary complexity. If you also need to add explicit proxy authentication, that is done in the one frontend explicit proxy configuration. Use the settings below to create an explicit proxy LTM configuration. If not mentioned, settings can be left as defaults. Under SSL Orchestrator -> Configuration in the UI, click on the gear icon in the top right corner. This will expose the DNS resolver configuration. The easiest option here is to select "Local Forwarding Nameserver" and then enter the IP address of the local DNS service. Click "Save & Next" and then "Deploy" when you're done. Under Network -> Tunnels in the UI, click Create. This will create a TCP tunnel for the explicit proxy traffic. Profile: select tcp-forward Under Local Traffic -> Profiles -> Services -> HTTP in the UI, click Create. This will create the HTTP explicit proxy profile. Proxy Mode: Explicit Explicit Proxy: DNS Resolver: select the ssloGS-net-resolver Explicit Proxy: Tunnel Name: select the TCP tunnel created earlier Under Local Traffic -> Virtual Servers, click Create. This will create the client-facing explicit proxy virtual server. Type: Standard Source: 0.0.0.0/0 Destination: enter an IP the client can use to access the explicit proxy interface Service Port: enter the explicit proxy listener port (ex. 3128, 8080) HTTP Profile: HTTP explicit profile created earlier VLANs and Tunnel Traffic: set to "Enable on..." and select the client-facing VLAN Address Translation: enabled Port Translation: enabled Under Local Traffic -> Virtual Servers, click Create again. This will create the TCP tunnel virtual server. Type: Standard Source: 0.0.0.0/0 Destination: 0.0.0.0/0 Service Port: * VLANs and Tunnel Traffic: set to "Enable on..." and select the TCP tunnel created earlier Address Translation: disabled Port Translation: disabled iRule: select the SSLO switching iRule Default Persistence Profile: select ssl Note, make sure that Address and Port Translation are disabled before clicking Finished. Under Local Traffic -> iRules, click Create. This will create a small iRule for the explicit proxy VIP to forward non-HTTPS traffic through the TCP tunnel. Change "<name-of-TCP-tunnel-VIP>" to reflect the name of the TCP tunnel virtual server created in the previous step. when HTTP_REQUEST { virtual "/Common/<name-of-TCP-tunnel-VIP>" [HTTP::proxy addr] [HTTP::proxy port] } Add this new iRule to the explicit proxy virtual server. To test, point your explicit proxy client at the IP and port defined IP:port and give it a go. HTTP and HTTPS explicit proxy traffic arriving at the explicit proxy VIP will flow into the TCP tunnel VIP, where the SSLO switching rule will process traffic patterns and send to the appropriate backend SSL Orchestrator topology-as-function. Testing and Considerations Assuming you have the default topology defined in the switching iRule's RULE_INIT, and no traffic matching rules defined, all traffic from the client should pass effortlessly through that topology. If it does not, Ensure the named defined in the static::default_topology variable is the actual name of the topology, without the prepended "sslo_". Enable debug logging in the iRule and observe the LTM log (/var/log/ltm) for any anomalies. Worst case, remove the client facing VLAN from the frontend switching virtual server and attach it to one of your topologies, effectively bypassing the layered architecture. If traffic does not pass in this configuration, then it cannot in the layered architecture. You need to troubleshoot the SSL Orchestrator topology itself. Once you have that working, put the dummy VLAN back on the topology and add the client facing VLAN to the switching virtual server. Considerations The above provides a unique way to solve for complex architectures. There are however a few minor considerations: This is defined outside of SSL Orchestrator, so would not be included in the internal HA sync process. However, this architecture places very little administrative burden on the topologies directly. It is recommended that you create and sync all of the topologies first, then create the layered virtual server and iRules, and then manually sync the boxes. If you make any changes to the switching iRule (or CPM policy), that should not affect the topologies. You can initiate a manual BIG-IP HA sync to copy the changes to the peer. If upgrading to a new version of SSL Orchestrator (only), no additional changes are required. If upgrading to a new BIG-IP version, it is recommended to break HA (SSL Orchestrator 8.0 and below) before performing the upgrade. The external switching virtual server and iRules should migrate natively. Summary And there you have it. In just a few steps you've been able to reduce complexity and add capabilities, and along the way you have hopefully recognized the immense flexibility at your command.SSL Orchestrator Advanced Use Cases: Forward Proxy Authentication
Introduction F5 BIG-IP is synonymous with "flexibility". You likely have few other devices in your architecture that provide the breadth of capabilities that come native with the BIG-IP platform. And for each and every BIG-IP product module, the opportunities to expand functionality are almost limitless.In this article series we examine the flexibility options of the F5 SSL Orchestrator in a set of "advanced" use cases. If you haven't noticed, the world has been steadily moving toward encrypted communications. Everything from web, email, voice, video, chat, and IoT is now wrapped in TLS, and that's a good thing. The problem is, malware - that thing that creates havoc in your organization, that exfiltrates personnel records to the Dark Web - isn't stopped by encryption. TLS 1.3 and multi-factor authentication don't eradicate malware. The only reasonable way to defend against it is to catch it in the act, and an entire industry of security products are designed for just this task. But ironically, encryption makes this hard. You can't protect against what you can't see. F5 SSL Orchestrator simplifies traffic decryption and malware inspection, and dynamically orchestrates traffic to your security stack. But it does much more than that. SSL Orchestrator is built on top of F5's BIG-IP platform, and as stated earlier, is abound with flexibility. SSL Orchestrator Use Case: Forward Proxy Authentication Arguably, authentication is an easy one for BIG-IP, but I'm going to ease into this series slowly. There's no better place to start than with an examination of some of the many ways you can configure an F5 BIG-IP to authenticate user traffic. Forward Proxy Overview Forward proxy authentication isn't exclusive to SSL Orchestrator, but a vital component if you need to authenticate inspected outbound client traffic to the Internet. In this article, we are simply going to explore the act of authenticating in a forward proxy, in general. - how it works, and how it's applied. For detailed instructions on setting up Kerberos and NTLM forward proxy authentication, please see the SSL Orchestrator deployment guide. Let's start with a general characterization of "forward proxy" to level set. The semantics of forward and reverse proxy can change depending on your environment, but generally when we talk about a forward proxy, we're talking about something that controls outbound (usually Internet-bound) traffic. This is typically internal organizational traffic to the Internet. It is an important distinction, because it also implicates the way we handle encryption. In a forward proxy, clients are accessing remote Internet resources (ex. https://www.f5.com). For TLS to work, the client expects to receive a valid certificate from that remote resource, though the inspection device in the middle does not own that certificate and private key. So for decryption to work in an "SSL forward proxy", the middle device must re-issue ("forge") the remote server's certificate to the client using a locally-trusted CA certificate (and key). This is essentially how every SSL visibility product works for outbound traffic, and a native function of the SSL Orchestrator. Now, for any of this to work, traffic must of course be directed through the forward proxy, and there are generally two ways that this is accomplished: Explicit proxy - where the browser is configured to access the Internet through a proxy server. This can also be accomplished through auto-configuration scripts (PAC and WPAD). Transparent proxy - where the client is blissfully unaware of the proxy and simply routes to the Internet through a local gateway. It should be noted here that SSL visibility products that deploy at layer 2 are effectively limited to one traffic flow option, and lack the level of control that a true proxy solution provides, including authentication. Also note, BIG-IP forward proxy authentication requires the Access Policy Manager (APM) module licensed and provisioned. Explicit Forward Proxy Authentication The option you choose for outbound traffic flow will have an impact on how you authenticate that traffic, as each works a bit differently. Again, we're not getting into the details of Kerberos or NTLM here. The goal is to derive an essential understanding of the forward proxy authentication mechanisms, how they work, how traffic flows through them, and ultimately how to build them and apply them to your SSL Orchestrator configurations. And as each is different, let us start with explicit proxy. Explicit forward proxy authentication for HTTP traffic is governed by a "407" authentication model. In this model, the user agent (i.e. a browser) authenticates to the proxy server before passing any user request traffic to the remote server. This is an important distinction from other user-based authentication mechanisms, as the browser is generally limited in the types of authentication it can perform here (on the user's behalf). In fact most modern browsers, with some exceptions, are limited to the set of "Windows Integrated" methods (NTLM, Kerberos, and Basic). Explicit forward proxy authentication will look something like this: Figure: 407-based HTTPS and HTTP authentication The upside here is that the Windows Integrated methods are usually "transparent". That is, silently handled by the browser and invisible to the user. If you're logged into a domain-joined workstation with a domain user account, the browser will use this access to generate an NTLM token or fetch a Kerberos ticket on your behalf. If you build an SSL Orchestrator explicit forward proxy topology, you may notice it builds two virtual servers. One of these is the explicit proxy itself, listening on the defined explicit proxy IP and port. And the other is a TCP tunnel VIP. All client traffic arrives at the explicit proxy VIP, then wraps around through the TCP tunnel VIP. The SSL Orchestrator security policy, SSL configurations, and service chains are all connected to the TCP tunnel VIP. Figure: SSL Orchestrator explicit proxy VIP configuration As explicit proxy authentication is happening at the proxy connection layer, to do authentication you simply need to attach your authentication policy to the explicit proxy VIP. This is actually selected directly inside the topology configuration, Interception Rules page. Figure: SSL Orchestrator explicit proxy authentication policy selection But before you can do this, you must first create the authentication policy. Head on over to Access -> Profiles / Policies -> Access Profiles (Per-session policies), and click the Create button. Settings: Name: provide a unique name Profile Type: SWG-Explicit Profile Scope: leave it at 'Profile' Customization Type: leave it at 'Modern' Don't let the name confuse you. Secure Web Gateway (SWG) is not required to perform explicit forward proxy authentication. Click Finished to complete. You'll be taken back to the profile list. To the right of the new profile, click the Edit link to open a new tab to the Visual Policy Editor (VPE). Now, before we dive into the VPE, let's take a moment to talk about how authentication is going to work here. As previously stated, we are not going to dig into things like Kerberos or NTLM, but we still need something to authenticate to. Once you have something simple working, you can quickly shim in the actual authentication protocol. So let's do basic LocalDB authentication to prove out the configuration. Hop down to Access -> Authentication -> Local User DB -> Instances, and click Create New Instance. Create a simple LocalDB instance: Settings: Name: provide a unique name Leave the remaining settings as is and click OK. Now go to Access -> Authentication -> Local User DB -> Users, and click Create New User. Settings: User Name: provide a unique user name Password: provide a password Instances: selected the LocalDB instance Leave everything else as is and click OK. Now go back to the VPE. You're ready to define your authentication policy. With some exceptions, most explicit forward proxy authentication policies will minimally include a 407 Proxy-Authenticate agent and an authentication agent. The 407 Proxy-Authenticate agent will issue the 407 Proxy-Authenticate response to the client, and pass the user's submitted authentication data (Basic Authorization header, NTLM token, Kerberos ticket) to the auth agent behind it. The auth agent is then responsible for validating that submission and allowing (or denying) access. Since we're using a simple LocalDB to test this, we'll configure this for Basic authentication. Figure: 407-based SWG-Explicit authentication policy 407 HTTP Response Agent Settings: Properties Basic Auth: enter unique text here HTTP Auth Level: select Basic Branch Rules Delete the existing Negotiate Branch Authentication Agent Settings: Type: LocalDB Auth LocalDB Instance: your Local DB instance Note again that this is a simple explicit forward proxy test using a local database for HTTP Basic authentication. Once you have this working, it is super easy to replace the LocalDB method with the authentication protocol you need. Now head back to your SSL Orchestrator explicit proxy configuration. Navigate to the Interception Rules page. On that page you will see a setting for Access Profile. Select your SWG-Explicit access policy here. And that's it. Deploy the configuration and you're done. Configure your browser to point to the SSL Orchestrator explicit proxy IP and port, if you haven't already, and attempt to access an external URL (ex. https://www.f5.com). Since this is configured for HTTP Basic authentication, you should see a popup dialog in the browser requesting username and password. Enter the values you created in the LocalDB user properties. In following articles, I will show you how to configure Kerberos and NTLM for forward proxy authentication. If you want to see what this communication actually looks like on the wire, you can either enable your browser's developer tools, network tab. Or for a cleaner view, head over to a command line on your client and use the cURL command (you'll need cURL installed on your workstation): curl -vk --proxy [PROXY IP:PORT] https://www.example.com --proxy-basic --proxy-user '[username:password]' Figure: cURL explicit proxy output What you see in the output should look pretty close to the explicit proxy diagram from earlier. And if your SSL Orchestrator security policy is defined to intercept TLS, you will see your local CA as the example.com CA issuer. Transparent Forward Proxy Authentication I intentionally started with explicit proxy authentication because it's usually the easiest to get your head around. Transparent forward proxy authentication is a bit different, but you very likely see it all the time. If you've ever connected to hotel, airport/airplane, or coffee shop WiFi, and you were presenting with a webpage or popup screen that asked for username, room number, or asked you to agree to some terms of use, you were using transparent authentication. In this case though, it is commonly referred to as a "Captive Portal". Note that captive portal authentication was introduced to SSL Orchestrator in version 6.0. Captive portal authentication basically works like this: On first time connecting, you navigate to a remote URL (ex. www.f5.com), which passes through a security device (a proxy server, or in the case of hotel/coffee shop WiFi, an access point). The device has never seen you before, so issues an HTTP redirect to a separate URL. This URL will present an authentication point, usually a web page with some form of identity verification, user agreement, etc. You do what you need to do there, and the authentication page redirects you back to the original URL (ex. www.f5.com) and either stores some information about you, or sends something back with you in the redirect (a token). On passing back through the proxy (or access point), you are recognized as an authenticated user and allowed to pass. The token is stored for the life of your sessions so that you are not sent back to the captive portal. Figure: Captive-portal Authentication Process The real beauty here is that you are not at limited in the mechanisms you use to authenticate, like you are in an explicit proxy. The captive portal URL is essentially a webpage, so you could use NTLM, Kerberos, Basic, certificates, federation, OAuth, logon page, basically anything. Configuring this in APM is also super easy. Head on over to Access -> Profiles / Policies -> Access Profiles (Per-session policies), and click the Create button. Settings: Name: provide a unique name Profile Type: SWG-Transparent Profile Scope: leave it at 'Named' Named Scope: enter a unique value here (ex. SSO) Customization Type: set this to 'Standard' Again, don't let the name confuse you. Secure Web Gateway (SWG) is not required to perform transparent forward proxy authentication. Click Finished to complete. You'll be taken back to the profile list. To the right of the new profile, click the Edit link to open a new tab to the Visual Policy Editor (VPE). We are going to continue to use the LocalDB authentication method here to keep the configuration simple. But in this case, you could extend that to do Basic authentication or a logon page. If you do Basic, Kerberos, or NTLM, you'll be using a "401 authentication model". This is very similar to the 407 model, except that 401 interacts directly with the user. And again, this is just an example. Captive portal authentication isn't dependent on browser proxy authentication capabilities, and can support pretty much any user authentication method you can throw at it. Figure: 401-based SWG-Transparent authentication policy 401 Authentication Agent Settings: Properties Basic Auth: enter unique text here HTTP Auth Level: select Basic Branch Rules Delete the existing Negotiate Branch Authentication Agent Settings: Type: LocalDB Auth LocalDB Instance: your Local DB instance Now, there are a few additional things to do here. Transparent proxy (captive portal) authentication actually requires two access profiles. The authentication profile you just created gets applied to the captive port (authentication URL). You need a separate access profile on the proxy listener to redirect the user to the captive if no token exists for that user. As it turns out, an SSL Orchestrator security policy is indeed a type of access profile, so it simply gets modified to point to the captive portal URL. The 'named' profile scope you selected in the above authentication profile defines how the two profiles share user identity information, thus both with have a named profile scope, and must use the same named scope value (ex. SSO). You will now create the second access profile: Settings: Name: provide a unique name Profile Type: SSL Orchestrator Profile Scope: leave it at 'Named' Named Scope: enter a unique value here (ex. SSO) Customization Type: set this to 'Standard' Captive Portals: select 'Enabled' Primary Authentication URI: enter the URL of the captive portal (ex. https://login.f5labs.com) You now need to create a virtual server to hold your captive portal. This is the URL that users are redirected to for authentication (ex. https://login.f5labs.com). The steps are as follows: Create a certificate and private key to enable TLS Create a client SSL profile that contains the certificate and private key Create a virtual server Destination Address/Mask: enter the IP address that the captive portal URL resolves to Service Port: enter 443 HTTP Profle (Client): select 'http' SSL Profile (Client): select your client SSL profile VLANs and Tunnels: enable for your client-facing VLAN Access Profile: select your captive portal access profile Head back into your SSL Orchestrator outbound transparent proxy topology configuration, and go to the Interception Rules page. Under the 'Access Profile' setting, select your new SSL Orchestrator access profile and re-deploy. That's it. Now open a browser and attempt to access a remote resource. Since this is using Basic authentication with LocalDB, you should get prompted for username and password. If you look closely, you will see that you've been redirected to your captive portal URL. 401 Basic authentication is not connection based, so APM stores the user session information by client IP. If you do not get prompted for authentication, it's likely you have an active session already. Navigate to Access -> Overview -> Active Sessions. If you see your LocalDB user account name listed there, delete it and try again (close and re-open the browser). And there you have it. In just a few steps you've configured your SSL Orchestrator outbound topology to perform user authentication, and along the way you have hopefully recognized the immense flexibility at your command. Thanks.TLS Fingerprinting - a method for identifying a TLS client without decrypting
Hello, Kevin Stewart here. A while back someone asked an interesting question in the DevCentral forum about selecting a client SSL profile based on the device (ex. iOS, Android, Windows Phone). Normally you'd use a browser User-Agent HTTP header to identify the client user agent, but in this case, and based on the OSI model, you wouldn't be able to select an SSL profile (OSI layer 6) based on a User-Agent HTTP header (OSI layer 7), because at this point in time you don't yet have the layer 7 data - it's still encrypted. You could, however, use layer 3 or 4 data (IPs and ports), but that's generally not useful for identifying the client user agent. But there might still be a way... Lee Brotherston has discovered that during an SSL handshake, most client user agents (different browsers, Dropbox, Skype, etc.) will initiate an SSL handshake request in an ever-so-unique way. The ordered combination of TLS version, record TLS version, ciphersuites, compression options, list of extensions, elliptic curves and signature algorithms are all specific enough that you can actually build a signature based on that data, and the collection of signatures into a database. From that discovery Lee created a project called "tls-fingerprinting". Please check it out. Now certainly, a client's ClientHello could be modified to support different ciphersuites and other features, the same way you could spoof a User-Agent HTTP header. However this modification will often lower security by re-introducing previously unsupported options, or in many cases modification to the user agent's SSL parameters isn't easy or isn't possible. So given that we now have a new way to identify a user agent based on the client's ClientHello (the first message in the SSL handshake), I decided to re-visit the original DC forum request by integrating Lee's database into an iRules-based solution. The code example in the aforementioned thread just used the client's ciphersuite list, however, so today I'm going to expand on that and use all of the paramaters from the tls-fingerprinting database. Before we get started, I should mention two things: This article is going to be long (sorry about that), and We're going to break it down into a few phases, specifically Defining the values in the tls-fingerprinting signature Exporting and converting the tls-fingerprinting database to a BIG-IP external data group Creating a fingerprintTLS PROC iRule (name this "Library-Rule") Creating the caller iRule So let's get started. Defining the values in the tls-fingerprinting signature Here's an example signature entry in Lee's tls-fingerprinting database (JSON version): {"id": 0, "desc": "ThunderBird (v38.0.1 OS X)", "record_tls_version": "0x0301", "tls_version": "0x0303", "ciphersuite_length": "0x0016", "ciphersuite": "0xC02B 0xC02F 0xC00A 0xC009 0xC013 0xC014 0x0033 0x0039 0x002F 0x0035 0x000A", "compression_length": "1", "compression": "0x00", "extensions": "0x0000 0xFF01 0x000A 0x000B 0x0023 0x0005 0x000D 0x0015" , "e_curves": "0x0017 0x0018 0x0019" , "sig_alg": "0x0401 0x0501 0x0201 0x0403 0x0503 0x0203 0x0402 0x0202" , "ec_point_fmt": "0x00" } Broken down it looks like this: { "id": 0, "desc": "ThunderBird (v38.0.1 OS X)", "record_tls_version": "0x0301", "tls_version": "0x0303", "ciphersuite_length": "0x0016", "ciphersuite": "0xC02B 0xC02F 0xC00A 0xC009 0xC013 0xC014 0x0033 0x0039 0x002F 0x0035 0x000A", "compression_length": "1", "compression": "0x00", "extensions": "0x0000 0xFF01 0x000A 0x000B 0x0023 0x0005 0x000D 0x0015" , "e_curves": "0x0017 0x0018 0x0019" , "sig_alg": "0x0401 0x0501 0x0201 0x0403 0x0503 0x0203 0x0402 0x0202" , "ec_point_fmt": "0x00" } This is a pretty straight forward set of JSON key-value pairs. And if you're curious about what any of these values mean, I urge you to fire up Wireshark, open a browser to some HTTPS site, and then find a ClientHello message in the capture. You'll see all of these values and more, except for the first two, in that message. Our job then is to a) export the set of signatures to a BIG-IP external data group, and b) create an iRule that extracts all of these values from the client's ClientHello and compares those to the set of signatures in the data group. Of course iRules don't natively support JSON parsing, and while yes I could use iRulesLX for this, I decided to simply reformat the signatures in the data group to something more condusive to TCL iRules. Exporting and converting the tls-fingerprinting database to a BIG-IP external data group I don't really care about the "id" value, so I'll leave that out. And the "desc" field will be the value in the data group. The key will be the concatenation of all of the remaining fields. "signature_data" := "ThunderBird (v38.0.1 OS X)", I'm also going to remove the "0x" from the hex values, remove whitespace, and delimit each field with the plus (+) sign, so the resulting key for the above signature will look like this: 0301+0303+0016+C02BC02FC00AC009C013C01400330039002F0035000A+1+00+0000FF01000A000B00230005000D0015+001700180019+04010501020104030503020304020202+00 If any of the values don't exist (ex. the signature doesn't have a sig_alg value), that value is replaced with "@@@@" in the resulting key. Okay, so to convert the tls-fingerprinting database to a BIG-IP external data group, you have to: 1. Download it - the current JSON-based database is here: https://github.com/LeeBrotherston/tls-fingerprinting/blob/master/fingerprints/fingerprints.json. Copy that JSON data in whole to a local text file. The conversion script uses BASH, so you need a Linux or Mac box. I named the file 'fingerprint.db'. 2. Convert it - use the following BASH script to extract each of the fields from each of the signatures. I should warn you now that my sed/awk/grep foo isn't strong, so I borrowed a BASH JSON parser from here: https://gist.github.com/cjus/1047794 #!/bin/bash function jsonval () { ## description desc=`echo $1 | sed 's/\\\\\//\//g' | sed 's/[{}]//g' | awk -v k="text" '{n=split($0,a,","); for (i=1; i<=n; i++) print a[i]}' | sed 's/\"\:\"/\|/g' | sed 's/[\,]/ /g' | sed 's/\"//g' | grep -w "desc" |awk -F": " '{print $2}'` ## record_tls_version rect=`echo $1 | sed 's/\\\\\//\//g' | sed 's/[{}]//g' | awk -v k="text" '{n=split($0,a,","); for (i=1; i<=n; i++) print a[i]}' | sed 's/\"\:\"/\|/g' | sed 's/[\,]/ /g' | sed 's/\"//g' | grep -w "record_tls_version" |awk -F": " '{print $2}' |sed 's/0x//g'` if [ -z "$rect" ]; then rect="@@@@"; fi ## tls_version tlsv=`echo $1 | sed 's/\\\\\//\//g' | sed 's/[{}]//g' | awk -v k="text" '{n=split($0,a,","); for (i=1; i<=n; i++) print a[i]}' | sed 's/\"\:\"/\|/g' | sed 's/[\,]/ /g' | sed 's/\"//g' | grep -w "tls_version" |awk -F": " '{print $2}' |sed 's/0x//g'` if [ -z "$tlsv" ]; then tlsv="@@@@"; fi ## ciphersuite_length cipl=`echo $1 | sed 's/\\\\\//\//g' | sed 's/[{}]//g' | awk -v k="text" '{n=split($0,a,","); for (i=1; i<=n; i++) print a[i]}' | sed 's/\"\:\"/\|/g' | sed 's/[\,]/ /g' | sed 's/\"//g' | grep -w "ciphersuite_length" |awk -F": " '{print $2}' |sed 's/0x//g' |sed 's/ //g'` if [ -z "$cipl" ]; then cipl="@@@@"; fi ## ciphersuite ciph=`echo $1 | sed 's/\\\\\//\//g' | sed 's/[{}]//g' | awk -v k="text" '{n=split($0,a,","); for (i=1; i<=n; i++) print a[i]}' | sed 's/\"\:\"/\|/g' | sed 's/[\,]/ /g' | sed 's/\"//g' | grep -w "ciphersuite" |awk -F": " '{print $2}' |sed 's/0x//g' |sed 's/ //g'` if [ -z "$ciph" ]; then tlsv="ciph"; fi ## compression_length coml=`echo $1 | sed 's/\\\\\//\//g' | sed 's/[{}]//g' | awk -v k="text" '{n=split($0,a,","); for (i=1; i<=n; i++) print a[i]}' | sed 's/\"\:\"/\|/g' | sed 's/[\,]/ /g' | sed 's/\"//g' | grep -w "compression_length" |awk -F": " '{print $2}'` if [ -z "$coml" ]; then coml="@@@@"; fi ## compression comp=`echo $1 | sed 's/\\\\\//\//g' | sed 's/[{}]//g' | awk -v k="text" '{n=split($0,a,","); for (i=1; i<=n; i++) print a[i]}' | sed 's/\"\:\"/\|/g' | sed 's/[\,]/ /g' | sed 's/\"//g' | grep -w "compression" |awk -F": " '{print $2}' |sed 's/0x//g' |sed 's/ //g'` if [ -z "$comp" ]; then comp="@@@@"; fi ## extensions exte=`echo $1 | sed 's/\\\\\//\//g' | sed 's/[{}]//g' | awk -v k="text" '{n=split($0,a,","); for (i=1; i<=n; i++) print a[i]}' | sed 's/\"\:\"/\|/g' | sed 's/[\,]/ /g' | sed 's/\"//g' | grep -w "extensions" |awk -F": " '{print $2}' |sed 's/0x//g' |sed 's/ //g'` if [ -z "$exte" ]; then exte="@@@@"; fi ## e_curves ecur=`echo $1 | sed 's/\\\\\//\//g' | sed 's/[{}]//g' | awk -v k="text" '{n=split($0,a,","); for (i=1; i<=n; i++) print a[i]}' | sed 's/\"\:\"/\|/g' | sed 's/[\,]/ /g' | sed 's/\"//g' | grep -w "e_curves" |awk -F": " '{print $2}' |sed 's/0x//g' |sed 's/ //g'` if [ -z "$ecur" ]; then ecur="@@@@"; fi ## sig_alg siga=`echo $1 | sed 's/\\\\\//\//g' | sed 's/[{}]//g' | awk -v k="text" '{n=split($0,a,","); for (i=1; i<=n; i++) print a[i]}' | sed 's/\"\:\"/\|/g' | sed 's/[\,]/ /g' | sed 's/\"//g' | grep -w "sig_alg" |awk -F": " '{print $2}' |sed 's/0x//g' |sed 's/ //g'` if [ -z "$siga" ]; then siga="@@@@"; fi ## ec_point_fmt ecfp=`echo $1 | sed 's/\\\\\//\//g' | sed 's/[{}]//g' | awk -v k="text" '{n=split($0,a,","); for (i=1; i<=n; i++) print a[i]}' | sed 's/\"\:\"/\|/g' | sed 's/[\,]/ /g' | sed 's/\"//g' | grep -w "ec_point_fmt" |awk -F": " '{print $2}' |sed 's/0x//g' |sed 's/ //g'` if [ -z "$ecfp" ]; then ecfp="@@@@"; fi echo "\"$rect+$tlsv+$cipl+$ciph+$coml+$comp+$exte+$ecur+$siga+$ecfp\" := \"$desc\"," } IFS=} for i in `cat fingerprint.db`; do jsonval $i done Create this BASH script however you like (VI, VIM, Joe, Nano, whatever), save it, chmod it so that it'll execute ('chmod 755 parser.sh'), and then run it ('./parser.sh'). It'll just echo the reformatted signatures to the screen, so you'll want to capture that as a file ('./parser.sh > fingerprint.dg'). It's also be a little slow, again due to my aggregious lack of sed/awk/grep (and regex) foo, but it should still finish in less than a minute. 3. Import it - now go to the BIG-IP management UI, and under System - File Management - Data Group File List, click Import. Choose your reformatted text file, give it a meaningful name (ex. fingerprint_db), select "String" as the File Contents type, and use the same name (ex. fingerprint_db) in the Data Group Name field. On a v12 BIG-IP this will auto-create the local data group. On earlier systems you'll need to go manually create the local data group object that points to this external data group. Creating a fingerprintTLS PROC iRule So now that we've reformatted and imported the fingerprintTLS database, let's build the iRule to parse out the data from the client's ClientHello. I should also warn you that this process requires a lot of binary manipulation, so please don't try to ingest it all at once if you're new to iRules. I'm building this iRule as a separate PROC that other data plane iRules can call. It won't be directly attached to a virtual server. ## Library-Rule ## TLS Fingerprint Procedure ################# ## ## Author: Kevin Stewart, 12/2016 ## Derived from Lee Brotherston's "tls-fingerprinting" project @ https://github.com/LeeBrotherston/tls-fingerprinting ## Purpose: to identify the user agent based on unique characteristics of the TLS ClientHello message ## Input: ## Full TCP payload collected in CLIENT_DATA event of a TLS handshake ClientHello message ## Record length (rlen) ## TLS outer version (outer) ## TLS inner version (inner) ## Client IP ## Server IP ############################################## proc fingerprintTLS { payload rlen outer inner clientip serverip } { ## The first 43 bytes of a ClientHello message are the record type, TLS versions, some length values and the ## handshake type. We should already know this stuff from the calling iRule. We're also going to be walking the ## packet, so the field_offset variable will be used to track where we are. set field_offset 43 ## The first value in the payload after the offset is the session ID, which may be empty. Grab the session ID length ## value and move the field_offset variable that many bytes forward to skip it. binary scan ${payload} @${field_offset}c sessID_len set field_offset [expr {${field_offset} + 1 + ${sessID_len}}] ## The next value in the payload is the ciphersuite list length (how big the ciphersuite list is. We need the binary ## and hex values of this data. binary scan ${payload} @${field_offset}S cipherList_len binary scan ${payload} @${field_offset}H4 cipherList_len_hex set cipherList_len_hex_text ${cipherList_len_hex} ## Now that we have the ciphersuite list length, let's offset the field_offset variable to skip over the length (2) bytes ## and go get the ciphersuite list. Multiple by 2 to get the number of appropriate hex characters. set field_offset [expr {${field_offset} + 2}] set cipherList_len_hex [expr {${cipherList_len} * 2}] binary scan ${payload} @${field_offset}H${cipherList_len_hex} cipherlist ## Next is the compression method length and compression method. First move field_offset to skip past the ciphersuite ## list, then grab the compression method length. Then move field_offset past the length (2) bytes and grab the ## compression method value. Finally, move field_offset past the compression method bytes. set field_offset [expr {${field_offset} + ${cipherList_len}}] binary scan ${payload} @${field_offset}c compression_len #set field_offset [expr {${field_offset} + ${compression_len}}] set field_offset [expr {${field_offset} + 1}] binary scan ${payload} @${field_offset}H[expr {${compression_len} * 2}] compression_type set field_offset [expr {${field_offset} + ${compression_len}}] ## We should be in the extensions section now, so we're going to just run through the remaining data and ## pick out the extensions as we go. But first let's make sure there's more record data left, based on ## the current field_offset vs. rlen. if { [expr {${field_offset} < ${rlen}}] } { ## There's extension data, so let's go get it. Skip the first 2 bytes that are the extensions length set field_offset [expr {${field_offset} + 2}] ## Make a variable to store the extension types we find set extensions_list "" ## Pad rlen by 1 byte set rlen [expr ${rlen} + 1] while { [expr {${field_offset} <= ${rlen}}] } { ## Grab the first 2 bytes to determine the extension type binary scan ${payload} @${field_offset}H4 ext ## Store the extension in the extensions_list variable append extensions_list ${ext} ## Increment field_offset past the 2 bytes of the extension type set field_offset [expr {${field_offset} + 2}] ## Grab the 2 bytes of extension lenth binary scan ${payload} @${field_offset}S ext_len ## Increment field_offset past the 2 bytes of the extension length set field_offset [expr {${field_offset} + 2}] ## Look for specific extension types in case these need to increment the field_offset (and because we need their values) switch $ext { "000b" { ## ec_point_format - there's another 1 byte after length ## Grab the extension data binary scan ${payload} @[expr {${field_offset} + 1}]H[expr {(${ext_len} - 1) * 2}] ext_data set ec_point_format ${ext_data} } "000a" { ## elliptic_curves - there's another 2 bytes after length ## Grab the extension data binary scan ${payload} @[expr {${field_offset} + 2}]H[expr {(${ext_len} - 2) * 2}] ext_data set elliptic_curves ${ext_data} } "000d" { ## sig_alg - there's another 2 bytes after length ## Grab the extension data binary scan ${payload} @[expr {${field_offset} + 2}]H[expr {(${ext_len} - 2) * 2}] ext_data set sig_alg ${ext_data} } default { ## Grab the otherwise unknown extension data binary scan ${payload} @${field_offset}H[expr {${ext_len} * 2}] ext_data } } ## Increment the field_offset past the extension data length. Repeat this loop until we reach rlen (the end of the payload) set field_offset [expr {${field_offset} + ${ext_len}}] } } ## Now let's compile all of that data. set cipl [string toupper ${cipherList_len_hex_text}] set ciph [string toupper ${cipherlist}] set coml ${compression_len} set comp [string toupper ${compression_type}] if { ( [info exists extensions_list] ) and ( ${extensions_list} ne "" ) } { set exte [string toupper ${extensions_list}] } else { set exte "@@@@" } if { ( [info exists elliptic_curves] ) and ( ${elliptic_curves} ne "" ) } { set ecur [string toupper ${elliptic_curves}] } else { set ecur "@@@@" } if { ( [info exists sig_alg] ) and ( ${sig_alg} ne "" ) } { set siga [string toupper ${sig_alg}] } else { set siga "@@@@" } if { ( [info exists ec_point_format] ) and ( ${ec_point_format} ne "" ) } { set ecfp [string toupper ${ec_point_format}] } else { set ecfp "@@@@" } ## Initialize the match variable set match "" ## Now let's build the fingerprint string and search the database set fingerprint_str "${outer}+${inner}+${cipl}+${ciph}+${coml}+${comp}+${exte}+${ecur}+${siga}+${ecfp}" ## Un-comment this line to display the fingerprint string in the LTM log for troubleshooting ## log local0. "${clientip}-${serverip}: fingerprint_str = ${fingerprint_str}" if { [class match ${fingerprint_str} equals fingerprint_db] } { ## Direct match set match [class match -value ${fingerprint_str} equals fingerprint_db] } elseif { not ( ${ciph} starts_with "C0" ) and not ( ${ciph} starts_with "00" ) } { ## Hmm.. there's no direct match, which could either mean a database entry doesn't exist, or Chrome (and Opera) are adding ## special values to the cipherlist, extensions list and elliptic curves list. ## ex. 9A9A, 5A5A, EAEA, BABA, etc. at the beginning of the cipherlist ## Let's strip out these anomalous values and try the match again. ## Substract 2 bytes from cipherlist length set cipl [format %04x [expr [expr 0x${cipl}] - 2]] ## Subtract 2 bytes from the front of the cipher list set ciph [string range ${ciph} 4 end] ## Subtract 2 bytes from the front of the extensions list set exte [string range ${exte} 4 end] ## There might be an additional random set in the string that needs to be removed (pattern is "(.)A\1A") regsub {(.)A\1A} ${exte} "" exte ## If the above regsub doesn't work, try the following: #regsub {(\wA)\1} ${exte} "" exte ## Subtract 2 bytes from the front of the elliptic curves list set ecur [string range ${ecur} 4 end] ## Rebuild the fingerprint string set fingerprint_str "${outer}+${inner}+${cipl}+${ciph}+${coml}+${comp}+${exte}+${ecur}+${siga}+${ecfp}" if { [class match ${fingerprint_str} equals fingerprint_db] } { ## Guess match set match [class match -value ${fingerprint_str} equals fingerprint_db] } else { ## No match set match "" } } ## Return the matching user agent string return ${match} } The PROC requires as input the full TCP payload (of the ClientHello message), the record length (extracted from the ClientHello message), the "outer" record TLS version and "inner" TLS version (also extracted form the ClientHello message). Using these values the PROC basically walks the payload looking for each of the required values (ciphersuite length, ciphersuite list, compression length, compression list, extensions list, elliptic curves, signature algorithms, and ec point formats). If any value doesn't exist in the payload (ex. the ClientHello doesn't contain a Sig_Alg field), that value is replaced with "@@@@". Once all of the values are found, the fingerprint string is created and used to search the data group. If there's a match, the user agent string (ex. ThunderBird (v38.0.1 OS X)) is returned to the caller. While testing this I noticed that newer versions of Chrome and Opera added what looked like "markers" to the ciphersuite list, extensions list, and elliptic curves list (ex. 9A9A, 5A5A, EAEA, BABA - always some alphanumeric value, followed by 'A', and repeated.). A cursory search didn't explain what these are, so maybe someone will know and report back. In the meantime, I added a "guess" function that removed these markers and tried the data group search again. All of the desktop browser testing (including Chrome and Opera) did get an accurate match with either the direct or guessed fingerprint, so I'll leave that in there until I find a better way to handle the markers. Creating the caller iRule The only thing left to do is to create the caller iRule. This iRule only needs to detect an SSL/TLS ClientHello, and then pass that to the fingerprint PROC. This is just a stub iRule to show the proper implementation. Once you've determined a TCP packet is an SSL/TLS handshake ClientHello, call the PROC and then do something useful with the resulting user agent string, like switch the client SSL profile. when CLIENT_ACCEPTED { ## Collect the TCP payload TCP::collect } when CLIENT_DATA { ## Get the TLS packet type and versions if { ! [info exists rlen] } { binary scan [TCP::payload] cH4ScH6H4 rtype outer_sslver rlen hs_type rilen inner_sslver if { ( ${rtype} == 22 ) and ( ${hs_type} == 1 ) } { ## This is a TLS ClientHello message (22 = TLS handshake, 1 = ClientHello) ## Call the fingerprintTLS proc set fingerprint [call Library-Rule::fingerprintTLS [TCP::payload] ${rlen} ${outer_sslver} ${inner_sslver} [IP::client_addr] [IP::local_addr]] ### Do Something here ### log local0. "match = ${fingerprint}" ### Do Something here ### } } # Collect the rest of the record if necessary if { [TCP::payload length] < $rlen } { TCP::collect $rlen } ## Release the paylaod TCP::release } What happens if there's no match? Yes, there are some caveats... It's safe to say that the tls-fingerprinting database isn't all inclusive. In fact it's FAR FROM COMPLETE and not always exact.I found, for example, that my version of Dropbox on a Win7 box (v16.4.30) doesn't make a match. It's nearly impossible to have the signature for every unique user agent every created, and all of the variations and versions of that agent. But what the database does have is the signatures for most browsers, so at the very least it makes for a nice way to whitelist browsers (vs. other agents). It also doesn't technically resolve the question in the original DC forum thread. The question was how to identify the device (ie. iOS, Android, Windows Phone), and for that you'd need some specific agent loaded on the device (not a browser) that could report that information. Mobile device management (MDM) solutions are particularly good at that sort of thing. The browser, Dropbox or other user agent on the mobile device may not specifically report the device (ex. "for iOS"). Some do, but I've found that most don't. At the end of this aticle I've included a few signatures that I found in my testing that aren't in the database. If your curious, uncomment thelog local0. "${clientip}-${serverip}: fingerprint_str = ${fingerprint_str}"line in the fingerprintTLS PROC and then tail the LTM log. The caller iRule is already logging the returned user agent string, so if that is empty, you'll see the empty match in the log (match =), preceded by the unmatched signature. Where this project may be most useful is in outbound traffic management, where you want to decrypt and inspect the Internet-bound traffic, but cannot decrypt some user agents becuase of things like cerificate pinning. Since the pinning decision happens at the client, the only other recourse is to bypass decryption and inspection based on the destination host name or IP address, which can be a tedious thing to manage. TLS fingerprinting might allow you to simply decrypt and inspect for the user agents that you know aren't affected by pinning, specifically browsers. You'll potentially miss some things that you could have decrypted, but you'll save yourself the burden of managing an ever-growing list of pinner exclusions. And on a final note, binary iRule manipulation is a very CPU-intensive thing to do. I could have very simply converted the raw payload to one long hex string (once) and walked that with string tools. I'll update the code when I have some time. Thanks. - Kevin Additional Signatures "0301+0303+0028+C02BC02F009ECC14CC13C00AC009C013C014C007C011003300320039009C002F0035000A00050004+1+00+0000FF01000A000B0023755000050012000D+001700180019+04010501020104030503020304020202+00" := "Dropbox", "0301+0303+0028+C02BC02F009ECC14CC13C00AC009C013C014C007C011003300320039009C002F0035000A00050004+1+00+0000FF01000A000B002300050012000D+001700180019+04010501020104030503020304020202+00" := "Dropbox", "0301+0303+001A+C030C028C014C02FC027C013009F006B0039009E0067003300FF+1+00+0000000B000A0023000D+00170019001C001B0018001A0016000E000D000B000C0009000A+060106020603050105020503040104020403030103020303020102020203+000102" := "Dropbox", "0301+0303+0094+C030C02CC032C02EC02FC02BC031C02D00A500A300A1009F00A400A200A0009EC028C024C014C00AC02AC026C00FC005006B006A006900680039003800370036C027C023C013C009C029C025C00EC00400670040003F003E0033003200310030C012C008C00DC00300880087008600850045004400430042001600130010000D009D009C003D0035003C002F00840041000A00FF+1+00+000B000A0023000D0015+00170019001C001B0018001A0016000E000D000B000C0009000A+060106020603050105020503040104020403030103020303020102020203+000102" := "Dropbox", "0301+0303+0028+C02BC02CC02FC030009E009FC009C00AC013C01400330039C007C011009C009D002F0035000500FF+1+00+0000000B000A0023000D+000E000D0019000B000C00180009000A00160017000800060007001400150004000500120013000100020003000F00100011+060106020603050105020503040104020403030103020303020102020203+000102" := "Android Google API Access", "0301+0303+001E+CC14CC13C02BC02F009EC00AC0140039C009C0130033009C0035002F000A+1+00+FF01000000170023000D0005337400120010000B000A+00170018+0601060305010503040104030301030302010203+00" := "Chrome 47.0.2526.83", "0301+0303+001E+CC14CC13C02BC02F009EC00AC0140039C009C0130033009C0035002F000A+1+00+FF01000000170023000D0005337400120010000B000A+00170018+0601060305010503040104030301030302010203+00" := "Chrome 48.0.2564.97", "0301+0303+001E+CC14CC13C02BC02F009EC00AC0140039C009C0130033009C0035002F000A+1+00+FF01000000170023000D00053374001200107550000B000A0015+00170018+0601060305010503040104030301030302010203+00" := "Chrome 48.0.2564.97", "0301+0303+0022+CCA9CCA8CC14CC13C02BC02FC02CC030C009C013C00AC014009C009D002F0035000A+1+00+FF01000000170023000D0005001200107550000B000A0018+001D00170018+06010603050105030401040302010203+00" := "Android Silk Browser", "0301+0303+0022+CCA9CCA8CC14CC13C02BC02FC02CC030C009C013C00AC014009C009D002F0035000A+1+00+FF01000000170023000D0005001200107550000B000A00180015+001D00170018+06010603050105030401040302010203+00" := "Android Silk Browser" "0303+0303+0038+C02CC02BC030C02F009F009EC024C023C028C027C00AC009C014C01300390033009D009C003D003C0035002F000A006A0040003800320013+1+00+0005000A000B000D0023001000175500FF01+001D00170018+040105010201040305030203020206010603+00" := "Internet Explorer 11.447.14393.0(Win 10)", "0301+0303+0022+C02BC02FC02CC030CCA9CCA8CC14CC13C009C013C00AC014009C009D002F0035000A+1+00+FF0100170023000D0005001200107550000B000A+001D00170018+06010603050105030401040302010203+00" := "Chrome 55.0.2883.87",SSL Orchestrator Advanced Use Cases: Local DNS Proxy Cache
Introduction F5 BIG-IP is synonymous with "flexibility". You likely have few other devices in your architecture that provide the breadth of capabilities that come native with the BIG-IP platform. And for each and every BIG-IP product module, the opportunities to expand functionality are almost limitless. In this article series we examine the flexibility options of the F5 SSL Orchestrator in a set of "advanced" use cases. If you haven't noticed, the world has been steadily moving toward encrypted communications. Everything from web, email, voice, video, chat, and IoT is now wrapped in TLS, and that's a good thing. The problem is, malware - that thing that creates havoc in your organization, that exfiltrates personnel records to the Dark Web - isn't stopped by encryption. TLS 1.3 and multi-factor authentication don't eradicate malware. The only reasonable way to defend against it is to catch it in the act, and an entire industry of security products are designed for just this task. But ironically, encryption makes this hard. You can't protect against what you can't see. F5 SSL Orchestrator simplifies traffic decryption and malware inspection, and dynamically orchestrates traffic to your security stack. But it does much more than that. SSL Orchestrator is built on top of F5's BIG-IP platform, and as stated earlier, is abound with flexibility. SSL Orchestrator Use Case: Local DNS Proxy Cache A basic tenet of an explicit proxy is DNS resolution. That is, the proxy functions to perform DNS requests on the client's behalf. This is a useful security characteristic as it abstracts DNS away from the client and generally prevents IP spoofing. For example, a client cannot spoof the IP of a known-bypassed host because an explicit proxy client does not control the IP address. The client passes a URL to the proxy, and the proxy resolves the URL to the correct address. Needless to say, however, if you have a thousand hosts perform 100 DNS requests per hour (each) in an environment, and you shift that to an explicit proxy, you now have a proxy server that's performing potentially 100,000 DNS requests per hour. Now fortunately, a large portion of the traffic from each of these clients will be going to the same places (ex. google.com), so the proxy server can locally cache a lot of these. But at some point, a dedicated DNS proxy cache can be useful to offload this burden, and in a configurable way. In an SSL Orchestrator environment, you may also have an explicit proxy security device plugged into a decrypted service chain, and that explicit proxy will also need DNS resolution. So if you've configured an SSL Orchestrator explicit proxy topology, and sending decrypted traffic to an explicit proxy in a service chain, you now have two devices that need DNS. As you've probably guessed by now, there's an elegant solution to this problem. Using a DNS cache profile on the BIG-IP, you can point the topology explicit proxy resolver, and the inline service resolver at the same cache. As traffic arrives at the topology, an initial DNS request flows to the DNS cache. If an answer doesn't exist, the request is forwarded to a defined authority and the answer cached. When the decrypted traffic arrives at the inline service, it attempts a DNS request to the same place and gets an immediate response from the cache. This has additional benefits in both optimizing traffic flow through the inline proxy device, as it doesn't have to wait for a DNS response from an external source, and also removes the need for this inline obfuscated security device to have to communicate outside of its secure enclave (for DNS). It may still have to communicate beyond the enclave for software, signature and licensing updates, but those are not real-time traffic concerns. This article provides a simple set of steps to build a local DNS proxy cache for SSL Orchestrator. [figure 1: SSL Orchestrator with DNS proxy cache] ** Note that a DNS proxy cache requires the DNS license, which also requires SSL Orchestrator to be licensed as an add-on to base LTM. ** Configuration Configuring a local DNS proxy cache involves creating the DNS cache and virtual server to hold it. This virtual server basically load balances external DNS and enables optimization through caching. You will point both the SSL Orchestrator resolver and the inline proxy DNS at this virtual server to take full benefit of the optimization. Also note that this could simply be used by an inline proxy service, in the absence of an explicit proxy SSL Orchestrator topology. This allows you to both optimize DNS for the inline proxy, and also not have to build a service control channel for inline proxy DNS to get out to an external DNS resource. Create DNS cache - Located under DNS -> Caches -> Cache List, click the Create button. Resolver Type: Transparent (None) Create DNS profile - Located under Local Traffic -> Profiles -> Services -> DNS, click the Create button. DNS Cache: Enabled DNS Cache Name: <above DNS cache> Create DNS proxy pool - This is the actual DNS resource (ex. 8.8.8.8:53). Find this under Local Traffic -> Pools. Create DNS proxy VIP (on XP service's outbound subnet) - This is the virtual server that load balances the DNS resource. Find this under Local Traffic Virtual Servers. It is important to create the inline proxy service first as that will establish the VLAN and IP subnet that this virtual server will attach to. Type: Standard Source Address: 0.0.0.0/0 Destination Address/Mask: select a unique IP address on the inline proxy service's outbound (from-service) subnet (ex. 198.19.96.153) Service Port: 53 Protocol: UDP Protocol Profile (Client): udp DNS Profile: select the previously-created DNS profile VLAN: select the inline proxy service's outbound (from-service) VLAN Source Address Translation: SNAT as required for routing Address Translation: enabled Port Translation: enabled Default Pool: select the DNS server pool Configure the SSL Orchestrator resolver to point to DNS proxy VIP - Navigate to the SSL Orchestrator UI and in the top right corner click on the gear icon to access the DNS resolver configuration. Enter this same virtual server IP address. Configure the inline explicit proxy service to point to the DNS proxy VIP - DNS requests will leave the inline proxy service on the service's from-service VLAN to the DNS proxy VIP. Optionally create a system route if the DNS pool requires a gateway route - If you need a route to get to the actual DNS resource, create a system route. This is found under Network -> Routes. To test, initiate a tcpdump capture on your outbound VLAN and look for port 53 traffic. Assuming an explicit proxy SSL Orchestrator topology, you should see a single outbound DNS request. The DNS request from the inline proxy device will be served directly from the newly cached data. tcpdump -lnni [outbound-vlan] port 53 And there you have it. In just a few steps you've configured your SSL Orchestrator security policy to take advantage of a local DNS proxy cache, and along the way you have hopefully recognized the immense flexibility at your command.
