Mitigating OWASP API Security Top 10 risks using F5 NGINX App Protect
This 2019 API Security article covers the summary of OWASP API Security Top 10 – 2019 categories and newly published 2023 API security article covered introductory part of newest edition of OWASP API Security Top 10 risks – 2023. We will deep-dive into some of those common risks and how we can protect our applications against these vulnerabilities using F5 NGINX App Protect. Excessive Data Exposure Problem Statement: As shown below in one of the demo application API’s, Personal Identifiable Information (PII) data, like Credit Card Numbers (CCN) and U.S. Social Security Numbers (SSN), are visible in responses that are highly sensitive. So, we must hide these details to prevent personal data exploits. Solution: To prevent this vulnerability, we will use the DataGuard feature in NGINX App Protect, which validates all response data for sensitive details and will either mask the data or block those requests, as per the configured settings. First, we will configure DataGuard to mask the PII data as shown below and will apply this configuration. Next, if we resend the same request, we can see that the CCN/SSN numbers are masked, thereby preventing data breaches. If needed, we can update configurations to block this vulnerability after which all incoming requests for this endpoint will be blocked. If you open the security log and filter with this support ID, we can see that the request is either blocked or PII data is masked, as per the DataGuard configuration applied in the above section. Injection Problem Statement: Customer login pages without secure coding practices may have flaws. Intruders could use those flaws to exploit credential validation using different types of injections, like SQLi, command injections, etc. In our demo application, we have found an exploit which allows us to bypass credential validation using SQL injection (by using username as “' OR true --” and any password), thereby getting administrative access, as below: Solution: NGINX App Protect has a database of signatures that match this type of SQLi attacks. By configuring the WAF policy in blocking mode, NGINX App Protect can identify and block this attack, as shown below. If you check in the security log with this support ID, we can see that request is blocked because of SQL injection risk, as below. Insufficient Logging & Monitoring Problem Statement: Appropriate logging and monitoring solutions play a pivotal role in identifying attacks and also in finding the root cause for any security issues. Without these solutions, applications are fully exposed to attackers and SecOps is completely blind to identifying details of users and resources being accessed. Solution: NGINX provides different options to track logging details of applications for end-to-end visibility of every request both from a security and performance perspective. Users can change configurations as per their requirements and can also configure different logging mechanisms with different levels. Check the links below for more details on logging: https://www.nginx.com/blog/logging-upstream-nginx-traffic-cdn77/ https://www.nginx.com/blog/modsecurity-logging-and-debugging/ https://www.nginx.com/blog/using-nginx-logging-for-application-performance-monitoring/ https://docs.nginx.com/nginx/admin-guide/monitoring/logging/ https://docs.nginx.com/nginx-app-protect-waf/logging-overview/logs-overview/ Unrestricted Access to Sensitive Business Flows Problem Statement: By using the power of automation tools, attackers can now break through tough levels of protection. The inefficiency of APIs to detect automated bot tools not only causes business loss, but it can also adversely impact the services for genuine users of an application. Solution: NGINX App Protect has the best-in-class bot detection technology and can detect and label automation tools in different categories, like trusted, untrusted, and unknown. Depending on the appropriate configurations applied in the policy, requests generated from these tools are either blocked or alerted. Below is an example that shows how requests generated from the Postman automation tool are getting blocked. By filtering the security log with this support-id, we can see that the request is blocked because of an untrusted bot. Lack of Resources & Rate Limiting Problem Statement: APIs do not have any restrictions on the size or number of resources that can be requested by the end user. Above mentioned scenarios sometimes lead to poor API server performance, Denial of Service (DoS), and brute force attacks. Solution: NGINX App Protect provides different ways to rate limit the requests as per user requirements. A simple rate limiting use case configuration is able to block requests after reaching the limit, which is demonstrated below. Server-Side Request Forgery Problem Statement: In an SSRF attack, vulnerable API endpoint within the application is targeted and attacker sends an unauthorized request allowing it to access internal resources. One of the common reasons for this is limited or lack of user input data validation. Example: In the demo application below, click on ‘Contact Mechanic’ and provide required details like Mechanic name, Problem Description and send Service Request. Below image shows that ‘contact_mechanic’ endpoint is internally making a call to ‘mechanic_api’ URL. Since ‘mechanic_api’ parameter accepts URL as data, this can be vulnerable to SSRF attacks. Exploiting the vulnerable endpoint by modifying ‘mechanic_api’ URL call to www.google.com in POST data call got accepted by returning 200 OK as response. This vulnerability can be misused to gain access to internal resources. Solution: To prevent this vulnerability, we will use the WAF API Security Policy in NGINX App Protect, which validates all the API request parameters and will block the suspicious requests consisting of irrelevant parameters, as shown below. Restricted/updated swagger file with .json extension is added as below: Policy used: App Protect API Security Retrying the vulnerability with ‘mechanic_api’ URL call to www.google.com in POST data now getting blocked. Validating the support ID in the security log below: Mass Assignment Problem Statement: API Mass Assignment vulnerability arises when clients can modify immutable internal object properties via crafted requests, bypassing API Endpoint restrictions. Attackers exploit this by sending malicious HTTP requests to escalate privileges, bypass security mechanisms, or manipulate the API Endpoint's functionality. Placing an order with quantity as 1: Bypassing API Endpoint restrictions and placing the order with quantity as -1 is also successful. Solution: To overcome this vulnerability, we will use the WAF API Security Policy in NGINX App Protect which validates all the API Security event triggered and based on the enforcement mode set in the validation rules, the request will either get reported or blocked, as shown below. Restricted/updated swagger file with .json extension is added as below: Policy used: App Protect API Security Re-attempting to place the order with quantity as -1 is getting blocked. Validating the support ID in Security log as below: Conclusion: In short, this article covered some common API vulnerabilities and shows how NGINX App Protect can be used as a mitigation solution to prevent these OWASP API security risks. Related resources for more information or to get started: F5 NGINX App Protect OWASP API Security Top 10 2019 OWASP API Security Top 10 2023Automating ACMEv2 Certificate Management on BIG-IP
While we often associate and confuse Let's Encrypt with ACMEv2, the former is ultimately a consumer of the latter. The "Automated Certificate Management Environment" (ACME) protocol describes a system for automating the renewal of PKI certificates. The ACME protocol can be used with public services like Let's Encrypt, but also with internal certificate management services. In this article we explore the more generic support of ACME (version 2) on the F5 BIG-IP.
7. SYN Cookie: Troubleshooting Stats
Introduction In this article I will explain what SYN Cookie stats you can consult and their meaning. There are more complex stats than the explained in this article but they are intended for helping F5 engineers when cases become complex. SYN Cookie stats First at all, in order to troubleshoot SYN Cookie you need to know how you can check SYN Cookie stats easily and understand what you are reading. The easiest way to see these stats in a device running LTM module based SYN Cookie is by running below command and focusing in SYN Cookies section of the output: # tmsh show ltm virtual <virtual> SYN Cookies Status full-hardware Hardware SYN Cookie Instances 6 Software SYN Cookie Instances 0 Current SYN Cache 2.0K SYN Cache Overflow 24 Total Software 4.3M Total Software Accepted 0 Total Software Rejected 0 Total Hardware 21.7M Total Hardware Accepted 3 Let’s go through each field to know what they means: Status: [full-software/full-hardware|not-activated]. This value describes what type of SYN Cookie mode has been activated, software or hardware. Once an attack has finished it is normal that LTM takes some time to deactivate SYN Cookie mode after attack traffic stops, see the second article in this series (SYN Cookie Operation). Note that we do not want SYN Cookie entering in an activating/deactivating loop in case TCP SYN packets per second reaching device are near to the configured SYN cache threshold. So delay of 30-60 seconds before SYN Cookie being deactivated is in normal range. Hardware SYN Cookie Instances: How many TMMs are under Hardware SYN Cookie mode. Software SYN Cookie Instances: How many TMMs are under Software SYN Cookie mode. It indicates if software is currently generating SYN cookies. Current SYN Cache: Indicates how many embryonic connections are handled by BIG-IP (refreshed every 2 seconds). SYN cache is always counting embryonic connections, regardless if SYN Cookie is activated or not. So even if SYN Cookies is completely turned off, we still have embryonic flows that have not been promoted to full flows yet (SYNs which has not completed 3WHS), this means that cache counter will still be used regularly, so is normal having a value different than 0. Disabling SYN Cookie will not avoid this counter increase but thresholds will not be taken into account. Since SYN cache is no longer a cache, as explained in prior articles, and the stat is merely a counter of embryonic flows, it does not consume memory resources. As the embryonic flows are promoted or time out, this value will decrease. SYN Cache Overflow (per TMM): It is incremented whenever the SYN cache threshold is exceeded and SYN cookies need to be generated. It increments in one per each TMM instance and this value is a counter that only increases, so we can consult the value to know how many times SYN Cookie has been activated since last stats reset, remember, per TMM. Total Software: Number of challenges generated by Software. This is increased regardless if client sends a response, does not send any response or the response is not correct. Total Software Accepted: Number of TCP handshakes that were correctly handled with clients. Total Software Rejected: Number of wrong responses to challenges. Remember that ALL rejected SYN cookies are in software, there is no hardware rejected. Total Hardware: Number of challenges generated by Hardware. Total Hardware Accepted: Number of TCP handshakes that were correctly handled with clients. In case you have configured AFM based SYN Cookie then you can use two easy sources of information, the already explained LTM command above, but also you can check stats for TCP half open DoS vector, at device or virtual server context, as you would do with any other DoS vector. Let’s check the most important fields at device context. # tmsh show security dos device-config | grep -A 40 half Statistics Type Count Status Ready Attack Detected 1 *Attacked Dst Detected 0 *Bad Actor Attack Detected 0 Aggregate Attack Detected 1 Attack Count 2 *Stats 1h Samples 0 Stats 408 *Stats Rate 408 Stats 1m 104 Stats 1h 0 Drops 1063 *Drops Rate 1063 Drops 1m 187 Drops 1h 4 *Int Drops 0 *Int Drops Rate 0 *Int Drops 1m 0 *Int Drops 1h 0 Status: This field confirm if this specific DoS vector is ready to detect TCP SYN flood attacks. You have to take into account that you could decide to configure this DoS vector with Auto-threshold, in which case AFM would be in charge of deciding the best threshold. Note that by enabling auto-threshold AFM would need some time to learn the traffic pattern of your environment, until it has enough information to create a correct threshold you will not see this field as Ready but as Learning. If vector is configured manually you always see it as Ready. Attack detected: It informs you if currently there is an ongoing attack and detected by AFM. Aggregate attack detected: Since DoS stats shown above are for device context the detected attack is aggregate. Attack Count: Gives information about how many attacks have been detected since stats were reset last time. It does not decrease. Stats: Number of embryonic connections at this current second. Remember that since this is a snapshot, the counter could go increase or decrease. This is different to other DoS vectors where it only increases. Stats 1m: Average of the Stats in the last minute. This is the average number of embryonic connections that AFM has seen when taking sampling every 1s. Stats 1h: Average of the Stats 1m in the last hour. Drops: It counts the number of wrong ACKs received. In other words this is the current snapshot of: Number of SYN Cookies – Number of validated ACKs received Drops 1m: Average of the Drops in the last minute Drops 1h: Average of the Drops 1m in the last hour I have added an asterisk to some fields to point to values that has not real meaning for SYN Cookie DoS vector, or information is not really useful from my perspective, but they are included to have coherence with other DoS attack stats information. Note: Detection logic for this vector is not based on the Stats 1m, as other DoS vectors, instead it is based on the current number of embryonic connections, that is, value seen in Stats counter. Interpreting stats Once you know what each important stat mean I will give some advises when you interpret SYN Cookie stats. You should know some of them already if you have read all articles in this series: Hardware can offload TMM for validation, so you can see a number of software generated SYN Cookies much bigger than software validated SYN Cookie since software generates cookies that are validated by hardware as well. Since it is possible that a software generated SYN Cookie be accepted by hardware and vice versa, hardware generated SYN Cookies be accepted by software, you could think that value for Total Software is the same than the result of adding the Total Software Accepted plus Total Software rejected. But that is NOT true since it can be possible that a SYN Cookie sent by BIG-IP does not have a response (ACK), quite typical during a SYN flood attack indeed. In this case nothing adds up because generated SYN Cookie was not accepted nor rejected. Remember that SYN cookie’s responses discarded by hardware will be rejected by software, so all rejects are in software. This is why there is not counter for Total Hardware rejected. This means that Total Software Rejected can be increase by Total Hardware. When there is an attack vectors definition that match this attack will be increased. So, for example, during a TCP SYN flood attack you will see that Stats increases for TCP half open and TCP SYN flood (maybe others like low TTL,... as well). Also Stats will increase in all contexts (device and virtual server). The first vector in an specific context whose limit is exceeded it will start to mitigate. This is important because in cases where TCP SYN flood DoS vector has a lower threshold than TCP half open DoS vector, you will notice that traffic is dropped but you did not expect this behavior. Check article 5 for more information. Example In this part you will learn what stats changes you should expect to see when a TCP SYN flood attack is detected and SYN Cookie is activated, so it starts to mitigate the attack. Let’s interpret below stats: During attack Status full-hardware Hardware SYN Cookie Instances 6 Software SYN Cookie Instances 0 Current SYN Cache 1 SYN Cache Overflow 24 Total Software 10.1K Total Software Accepted 0 Total Software Rejected 0 Total Hardware 165.1M Total Hardware Accepted 3 After attack Status not-activated Hardware SYN Cookie Instances 0 Software SYN Cookie Instances 0 Current SYN Cache 15 SYN Cache Overflow 24 Total Software 10.1K Total Software Accepted 0 Total Software Rejected 0 Total Hardware 171.0M Total Hardware Accepted 3 Before the attack, before SYN Cookie is activated, you will see Current SYN Cache stats starts to increase quickly since TCP SYN packets are causing an increment of embryonic connections. Once SYN Cache threshold has been reached in a TMM then SYN Cache Overflow will increase attending to the number of TMMs that detected the attack. In above example you see 24 because this is a 6 CPUs device and 4 TCP SYN Flood attacks were detected by SYN Cookie. Remember this counter will never decrease unless we reset stats. During attack SYN cookie is activated so Current SYN Cache will start to decrease until reaching 0 because SYN Cookie Agent starts to handle TCP 3WHS, in other words, TCP stack stops to receive TCP SYN packets. We can check how many TMMs have SYN cookie activated currently looking at Hardware/Software SYN Cookie Instances counter. Note this match with what I explained for SYN Cache Overflow value. Legitimate connections are counted under Total Hardware/Software Accepted. In this case, we can see that although several millions of TCP SYN packets reached the device only 3 TCP 3WHS were correctly carried out. As you can see this device has Hardware SYN Cookie configured and working, but you can read that software also generates SYN Cookie challenges (Total Software). As commented in article number six of these series, this is expected and can be due to collisions or due to validations of first challenges when SYN Cookie is activated and TMMs handles TCP SYN packets until it enables hardware to do it. This does not affect device performance. In order to change from ‘Status full-hardware’ to ‘Status not-activated’ both HSBs must exit from SYN Cookie mode. Conclusion Now you know how to interpret stats, so you know can deduce information about the past and the present status of your device related to SYN Cookie. In next two article I will end up this series and this troubleshooting part talking about traffic captures and meaning of logs.2. SYN Cookie: Operation
Introduction As concluded in the last article, in order to avoid allocating space for TCB, the attacked device needs to reject TCP SYN packets sent by clients. In this article I will explain how a system can do this without causing service disruption, and more specifically I will explain how this work in BIG-IP. Implementation Since attacked device need to alter default TCP 3WHS behaviour the best option is implementing SYN Cookie countermeasure in an intermediate device, so you offload your servers from this task. In this way if connection is not legitimate then it is just never forwarded to the backend server and therefore it will not waste any kind of extra resourcess. Since BIG-IP is already in charge of handling application traffic directed towards servers it is the best place to implement SYN Cookie. What BIG-IP does is adding an extra layer, which we can call SYN Cookie Agent, that basically implement a stateless buffer between client and BIG-IP TCP stack. This agent is in charge of handling client’s TCP SYN packets by modifying slightly the standard behaviour of TCP 3WHS, this modification comes in two flavours depending on what type of routing role BIG-IP is playing between client and server. Symmetric routing This is the typical situation. In this environment BIG-IP is sited in the middle of the TCP conversation and all the traffic from/to server pass through it. The SYN Cookie operation in this case is briefly described below: Client sends a TCP SYN packet to BIG-IP. BIG-IP uses a stateless buffer for answering each client SYN with a SYN/ACK. BIG-IP generates the 32 bits sequence number which will be included in SYN/ACK packet sent to the client. BIG-IP encodes essential and mandatory information of the connection in 24 bits. BIG-IP hashes the previous encoded information. BIG-IP also encodes other values like MSS in the remaining bits. BIG-IP generates the SYN/ACK response packet and includes the hash and other encoded information as sequence number for the packet. This is the so called SYN Cookie. BIG-IP sends SYN/ACK to client. BIG-IP discards the SYN from the stateless buffer, in other words, BIG-IP removes all information related to this TCP connection. At this point no memory has been allocated for TCP connection (TCB). Client sends correct ACK to BIG-IP acknowledging BIG-IP’s sequence number. BIG-IP validates ACK. BIG-IP subtracts one to this ACK. BIG-IP runs the hash function using connection information as input (see point 3-b above). Then it compares it with the hash provided in the ACK, if they match then it means client sent a correct SYN Cookie response and that client is legitimate. BIG-IP uses connection information in the ACK TCP/IP headers to create an entry in connflow. At this time is when BIG-IP builds TCB entry, so it's the first time BIG-IP uses memory to save connection information. BIG-IP increase related SYN Cookie stats. BIG-IP starts and complete a TCP 3WHS with backend server on behalf of the client since we are sure that client is legitimate. Now traffic for the connection is proxied by BIG-IP as usual attending to configured L4 profile in the virtual server. *If ACK packet received by BIG-IP is a spurious ACK then BIG-IP will discard it and no entry will be created in connection table. Since attackers will never send a correct response to a SYN/ACK then you can be sure that TCB entries are never created for them. Only legitimate clients will use BIG-IP resources as shown in diagram: Fig4. TCP SYN Flood attack with SYN Cookie countermeasure Asymmetric routing In an asymmetric environment, also called nPath or DSR, you face a different problem because Big-IP cannot establish a direct TCP 3WHS with the server (point 11 in last section). As you can see in below diagram SYN/ACK packet sent from server to client would not traverse Big-IP, so method used for symmetric routing cannot be used in this case. You need another way to trust in clients and discard them as attackers, so clients then can complete TCP 3WHS directly with the server. Fig5. TCP state diagram section for asymmetric routing + FastL4 In order to circumvent this problem BIG-IP takes the advantage of the fact that applications will try to start a second TCP connection if a first TCP 3WHS is RST by the server. What BIG-IP does in asymmetric routing environments is completing the TCP three way handshake with client, issuing SYN Cookie as I described for symmetric routing, and once BIG-IP confirms that client is trustworthy it will add its IP to SYN Cookie Whitelist, it will send a RST to the client and it will close the TCP connection. At this point client will try to start a new connection and this time BIG-IP will let the client talk directly to the server as it would do under normal circumstances (see diagram above). The process is briefly described below: Client sends a TCP SYN packet to BIG-IP. BIG-IP generates the sequence number as explained for symmetric routing. BIG-IP generates the SYN/ACK response packet and includes the calculated sequence number for the packet. BIG-IP sends SYN/ACK to client and then remove all information related to this TCP connection. At this point no memory has been allocated for TCP connection (TCB). Client sends correct ACK to BIG-IP acknowledging sequence number. BIG-IP validates ACK. BIG-IP substract one to this ACK so it can decode needed information and check hash. BIG-IP increase related SYN Cookie stats. BIG-IP sends a RST to client and discards TCP connection. Big-IP adds client’s IP to Whitelist. Clients starts a new TCP connection. BIG-IP lets client to start this new TCP connection directly to the server since it knows that server is legitimate. *If ACK packet received by BIG-IP is a spurious ACK then BIG-IP will discard it and no entry will be created in connection table. Fig6. TCP 3WHS flow in asymmetric routing DSR whitelist has some important characteristics you need to take into account: By default IP is added 30 seconds to the whitelist (DB Key tm.flowstate.timeout). Client’s IP is added to whitelist for 30 seconds but only if there is no traffic from this client, if BIG-IP have already seen ACK from this client then its IP is removed from whitelist since connection has been already established between client and server. Whitelist is common to all virtual servers, so if a client is whitelisted it will be for all applications. Whitelist it is not mirrored. Whitelist it is not shared among blades. SYN Cookie Challenge When a TCP connection is initiated the TCP SYN packet sent by the client specify certain values that define the connection, some of these values are mandatory, like source and destination IP and port, otherwise you would not be able to identify the correct connection when packets arrive. Some other values are optional and they are used to improve performance, like TCP options or WAN optimizations. Under normal circumstances, upon TCP SYN reception the system creates a TCB entry where all this information is saved. BIG-IP will use this information to set up the TCP connection with the backend server. The problem we face is that when SYN Cookie is in play device does not create the TCB entry, only a limited piece of connection information is collected, so the information that BIG-IP has about the TCP connection is limited. Remember that SYN Cookie is not handled by TCP stack but by the stateless SYN Cookie Agent, so we cannot save the connection details. What BIG-IP does instead is encoding key information in 24 bits, this left only some bits for the rest of data. While there is no room for values like Window Scale information, however we have space for other values, for example 3 bits reserved for MSS value. This limits MSS possible values to 8, the most commonly used values, and the one chosen will the nearest to the original MSS value. However, note that MSS limitation has a workaround through configuration in FastL4 profile that it can help in some cases. The option SYN Cookie MSS in this profile specifies a value that overrides the SYN cookie maximum segment size (MSS) value in the SYN-ACK packet that is returned to the client. Valid values are 0, and values from 256 through 9162. The default is 0, which means no override. You might use this option if backend servers use a different MSS value for SYN cookies than the BIG-IP system does. If this is not enough for some customers, BIG-IP overcomes this problem by using TCP timestamp space to save extra information about TCP connection, in other words we create a second extra SYN Cookie. This space is used to record the client and server side Window Scale values, or the SACK info which are then made available to the TCP stack via this cookie if the connection is accepted. Note that TCP connection will only be accepted if both SYN Cookies (standard and Timestamp) are correct. So all this means that if the client starts a connection with TCP TS set then Big-IP will have more space to encode information and hence the performance will be improved when under TCP SYN flood attack. NOTE: SYN Cookie Timestamp extension (software or hardware) only work for standard virtual servers currently. FastL4 virtual servers only supports MMS option in SYN Cookie mode. Deactivating In order to deactivate SYN Cookie three conditions need to be met, these conditions are the same for LTM or AFM SYN Cookie, although stat names can vary: Embryonic connections must be below the configured SYN Cookie threshold. The ratio of invalid packets has not been exceeded. We define this ratio as a percentage saved in the DB key dos.syncookiedeactivate which by default is the 50% of the configured threshold (do not change this value if it is not requested by a F5 engineer). The second condition above has to be met three consecutive times as a method for avoiding SYN Cookie activation/deactivation flapping. BIG-IP will receive information about the number of invalid packets every 7 seconds, so this means that at least 21 seconds are required to deactivate SYN Cookie assuming that the second condition is constantly met. Note the difference between embryonic connections and invalid connections in the above conditions: Embryonic connections are connections pending to be confirmed with a last ACK. Invalid connections include any connection that did not finish the TCP 3WHS with a correct last ACK, that is, connections for which BIG-IP did not receive the last ACK, or for which BIG-IP did receive a wrong ACK. Finally remember that for Hardware SYN Cookie all HSBs connected to TMM must exit from SYN Cookie mode in order to consider that the TMM exit SYN Cookie. And also all TMMs must exit from SYN Cookie mode in order to deactivate SYN Cookie completely for that context. Conclusion Now you know how SYN Cookie works under the hoods. In next article I will describe when SYN Cookie is activated and I will give specific details of BIG-IP SYN Cookie operation. Note that limitations related to SYN Cookie commented in this article are not caused specifically by BIG-IP SYN Cookie implementation but by SYN Cookie standard itself. In fact, F5 Networks implements some improvements on SYN Cookie to get a better performance and provide some extra features.F5 AI Gateway - Secure, Deliver and Optimize GenAI Apps
AI has revolutionized industries by automating tasks, enabling data-driven decisions, and enhancing efficiency and innovation. While it offers businesses a competitive edge by streamlining operations and improving customer experiences, it also introduces risks such as security vulnerabilities, data breaches, and cost challenges. Businesses must adopt robust cybersecurity measures and carefully manage AI investments to balance benefits with risks. F5 provides comprehensive controls to protect AI and IT infrastructures, ensuring sustainable growth in an AI-driven world. Welcome to F5 AI Gateway - a runtime security and traffic governance solutionAgentic RAG - Securing GenAI with F5 Distributed Cloud Services
Agentic RAG (Retrieval-Augmented Generation) enhances the capabilities of a GenAI chatbot by integrating dynamic knowledge retrieval into its conversational abilities, making it more context-aware and accurate. In this demo, I will focus on security aspect of the solution. This demonstration will highlight the various security measures implemented and enforced in our AI reference architecture for this Agentic RAG. F5 is a trusted leader in security, with a track record of delivering robust solutions for securing applications and networks. Recognized by many independent evaluations as a Leader in Web Application and API Security from IDC, SC Award, TrustRadius, EMA, and many more, F5 exemplifies excellence and innovation. These endorsements affirm F5’s expertise, reassuring organizations that their digital assets are protected by a capable, reputable partner that keeps pace with evolving security needs.Mitigating OWASP API Security Risk: Security Misconfiguration using F5 XC Platform
Overview This article is a continuation of the series of articles on OWASP API Security vulnerabilities and demonstrates a scenario for mitigating API Security Misconfiguration using F5 Distributed Cloud(XC) Platform. See F5 Distributed Cloud API Security dynamically discover and automatically protect API endpoints. Introduction to OWASP API Security Misconfiguration APIs are the backbone of the modern application development model and because of their heavy usage they often become victim of attacks. Sometimes these vulnerabilities arise if security best practices are missed and are not followed properly in application development life cycle. Below are a few scenarios which fall under API Security Misconfiguration category: Latest security patches are not applied. Unnecessary HTTP verbs are enabled exposing APIs to get accessed by them. Improper implementation of CORS policy. Missing repeatable security hardening process. Exposing detailed stack trace error messages or sensitive information. Problem Statement Improperly configured CORS policies can expose web applications to vulnerabilities, allowing malicious actors to perform unauthorized actions or access sensitive data. This poses significant risks to user privacy, application integrity, and organizational security. In the demonstration below we will cover a scenario where the application is vulnerable to CORS and will see how F5 Distributed Cloud WAAP can help in identifying and mitigating such threats. What is Cross-Origin Resource Sharing (CORS) ? CORS is a security feature implemented by browsers to allow or block web applications from making requests to domains other than their own. This mechanism helps prevent certain types of attacks, by ensuring that only authorized domains can access certain resources. CORS occurs only when the target server(cross-origin) is accessed from other domains and sub-domains. CORS works by specific HTTP/S headers that allow a server to explicitly specify which origins are allowed to access its resources and which methods and headers can be used. Preflight Request: When making cross-origin requests that are complex (i.e., requests that use non-simple methods, custom headers, or credentials), the browser sends an OPTIONS request before the actual request which is called the preflight request. The preflight request is used to check if the server will allow the actual request. Specifically, a preflight request occurs when a web page makes a cross-origin HTTP request that does not meet the simple request criteria defined by the CORS specification. Consider the scenario below, where authentication request in the origin server is handled by some third-party cross-origin server. If the cross-origin server is not configured to block untrusted origins based on domain, methods and headers, attacker can take advantage of this vulnerability by performing harmful action using methods and headers in requests. Users access the origin web server through web browser and enters the credentials for authentication. Authentication request will be transferred to cross-origin web server for authentication. Authentication request from origin contains non-simple header (X-Custom-Header), as per CORS specification browser sends a Preflight Request to cross-origin, with all the details of actual request. Cross-Origin responds back with Preflight Response where it’s allowing all the requests. Browser checks the preflight response and since all the requests are allowed, actual request containing the payload is sent to the cross-origin. Cross-Origin responds back with the authentication token. In this scenario, since all the origins, methods and custom headers are allowed by cross-origin, the attacker can craft a malicious request to modify or delete the content in cross-origin server from any origin server. Prevention using F5 XC: From the suite of security solutions offered by F5 Distributed Cloud(XC) WAAP, here we have chosen to create an ‘CORS Policy’ to allow only authorized requests. Pre-requisites: Create a Load Balancer in F5 XC and point the LB to the vulnerable web server by adding the server details in origin pool. For LB configuration steps, please follow the steps here. Configure CORS policy under “Common Security Controls” in LB to allow only authorized requests. For CORS configuration steps, please follow the steps here. *Allow Origin and Allow Origin Regex fields in F5 XC CORS configuration will be used to verify the Origins for CORS. Origins/Domains not listed won’t be blocked and continue to work normally. Note – Chrome browser is used throughout this demo The malicious activity which can be performed in the scenario discussed earlier can be mitigated by having the vulnerable cross-origin web server behind F5 XC . In F5 XC load balancer a CORS feature security policy must be configured to check origin, methods and customer headers based on security requirement. Users access the origin web server through web browser and enters the credentials for authentication. Authentication request will be transferred to cross-origin web server for authentication. Authentication request from origin contains non-simple header (X-Custom-Header), as per CORS specification browser sends a Preflight Request to cross-origin, with all the details of actual request. Fig 2.2 - Preflight request Highlighted sections will be part of Preflight Request sent to the cross-origin (target server) from the web browser. These values are extracted from the request made by the user. Since cross-origin is protected by F5 XC in this scenario, F5 XC responds with Preflight Response. Fig 2.3 - Preflight response As per our architecture shown in Fig 2, cross-origin (target server) is behind F5 XC which has a CORS policy configured. The highlighted section shows the Preflight Response sent from the F5 XC to the web browser based on the CORS configuration defined in F5 XC. The browser checks the preflight response sent from the F5 XC where all the non-simple methods and custom headers are blocked, web browser verifies this and drops the actual request. Fig 2.4 - Actual request blocked due to CORS Fig 2.5 - Preflight options call captured in F5 XC In the above screenshot, Preflight (OPTIONS) request made to load balancer (having target server) can be observed. The subsequent actual request is not present which is blocked by the browser based on CORS configuration. Conclusion In conclusion, ensuring that web applications are safeguarded against CORS vulnerabilities is not just a technical necessity—it's a critical step in protecting users and business. By using F5 XC WAAP solution, proactive control can be taken over security environment, preventing unauthorized cross-origin requests and safeguarding sensitive data from malicious actors. Further Reading Official W3C CORS specification CORS Reference OWASP API Security Project OWASP API7:2019 Security Misconfiguration F5 Distributed Cloud Services F5 Distributed Cloud WAAP Overview of OWASP API Security Top 10 2019Understanding The TikTok Ban, Salt Typhoon and More | AppSec Monthly January Ep.27
In this episode of AppSec Monthly, our host MegaZone is joined by m_heath, Merlyn Albery-Speyer, and AubreyKingF5, as they dive into the latest cybersecurity news. We explore the complexities of the TikTok ban, the impact of geopolitical decisions on internet freedom, and the nuances of data sovereignty. Our experts also discuss the implications of recent breaches by Chinese state actors and the importance of using end-to-end encrypted apps to protect your data. Additionally, we shed light on the fascinating history of internet control and how it continues to evolve with emerging technologies. Stay tuned until the end for insights on the upcoming VulnCon 2025 and how you can participate. Don’t forget to subscribe for more AppSec insights!Mitigating OWASP Web Application Security Top 10 – 2021 risks using F5 Distributed Cloud Platform
Overview: In the early 90’s, applications were in dormant phase and JavaScript & XML were dominating this technology. But in 1999, the first web application was introduced after the release of the Java language in 1995. Later with the adoption of new languages like Ajax, HTML, Node, Angular, SQL, Go, Python, etc. and availability of web application frameworks have boosted application development, deployment, and release to production. With the evolving software technologies, modern web applications are becoming more and more innovative, providing users with a grand new experience and ridiculously ease of interface. With these leading-edge technologies, novel exploit surfaces are also exposed which made them a primary target for intruders/hackers. Application safeguarding against all these common exploits is a necessary step in protecting backend application data. Open Worldwide Application Security Project (OWASP) is one of those security practices which protects application with above issues. This article is the first part of the series and covers OWASP evolution, its importance and overview of top 10 categories. Before diving into OWASP Web Application Security Top 10, let’s time travel to era of 1990’s and try to identify challenges the application customers, developers and users were facing. Below are some of them: Rapid and diversified cyber-attacks has become a major concern and monitoring/categorizing them was difficult Product owners are concerned about application security & availability and are in desperate need of a checklist/report to understand their application security posture Developers are looking for recommendations to securely develop code before running into security flaws in production No consolidated repo to manage, document and provide research insights for every security vulnerability After running into the above concerns, people across the globe have come together in 2001 and formed an international open-source community OWASP. It’s a non-profit foundation which has people from different backgrounds like developers, evangelist, security experts, etc. The main agenda for this community is to solve application related issues by providing: Regularly updating “OWASP TOP 10” report which provides insights of latest top 10 security issues in web applications Report also provides security recommendations to protect them from these issues Consolidated monitoring and tracking of application vulnerabilities Conducting events, trainings and conferences around the world to discuss, solve and provide preventive recommendations for latest security issues OWASP also provides security tools, research papers, libraries, cheat sheets, books, presentations and videos covering application security testing, secure development, and secure code review OWASP WEB SECURITY TOP 10 2021: With the rapid increase of cyber-attacks and because of dynamic report updates, OWASP gained immense popularity and is considered as one of the top security aspects which application companies are following to protect their modern applications against known security issues. Periodically they release their Top 10 vulnerabilities report and below are the latest Top 10 - 2021 categories with their summary: A01:2021-Broken Access Control Access controls enforce policy such that users cannot act outside of their intended permissions. Also called authorization, it allows or denies access to your application's features and resources. Misuse of access control enables unauthorized access to sensitive information, privilege escalation and illegal file executions. Check this article on protection against broken access vulnerabilities A02:2021-Cryptographic Failures In 2017 OWASP top 10 report, this attack was known as Sensitive Data Exposure, which focuses on failures related to cryptography leading to exposure of sensitive data. Check this article on cryptographic failures A03:2021-Injection An application is vulnerable to injection if user data and schema is not validated by the application. Some of the common injections are XSS, SQL, NoSQL, OS command, Object Relational Mapping (ORM), etc., causing data breaches and loss of revenue. Check this article on safeguarding against injection exploits A04:2021-Insecure Design During the development cycle, some phases might be reduced in scope which leads to some of the vulnerabilities. Insecure Design represents the weaknesses i.e., lack of security controls which are not tracked in other categories throughout the development cycle. Check this article on design flaws and mitigation A05:2021-Security Misconfiguration This occurs when security best practices are overlooked allowing attackers to get into the system utilizing the loopholes. XML External Entities (XXE), which was previously a Top 10 category, is now a part of security misconfiguration. Check this article on protection against misconfiguration vulnerabilities A06:2021-Vulnerable and Outdated Components Applications used in enterprises are prone to threats such as code injection, buffer overflow, command injection and cross-site scripting from unsupported, out of date open-source components and known exploited vulnerabilities. Utilizing components with security issues makes the application itself vulnerable. Intruders will take use of this defects and exploit the deprecated packages thereby gaining access to backend applications. Check this article on finding outdated components A07:2021-Identification and Authentication Failures Confirmation of the user's identity, authentication, authorization and session management is critical to protect applications against authentication-related attacks. Apps without valid authorization, use of default credentials and unable to detect bot traffic are some of the scenarios in this category. Check this article on identifying and protection against bots A08:2021-Software and Data Integrity Failures Software and data integrity failures occurs when updates are pushed to the deployment pipeline without verifying its integrity. Insecure Deserialization, which was a separate category in OWASP 2017, has now become a part of this larger category set. Check this article on software failures protection A09:2021-Security Logging and Monitoring Failures As a best recommendation, we shall always log all incoming request details and monitor application for fraudulent transactions, invalid logins, etc. to identify if there are any attacks or breaches. Applications without logging capabilities provide opportunities to the attackers to exploit the application and may lead to many security concerns. Without logging and monitoring we won’t be able to validate the application traffic and can’t identify the source of the breach. Check this article for identifying logging issues A10:2021-Server-Side Request Forgery Server-Side Request Forgery (SSRF) attack is a technique which allows intruders to manipulate the server-side application vulnerability and make a malicious request to the internal-only resources. Attacker exploits this flaw by modifying/crafting a URL which forces the server to retrieve and disclose sensitive information. Check this article which focusses on SSRF mitigation NOTE: This is an overview article of this OWASP series, check the below links to prevent these vulnerabilities using F5 Distributed Cloud Platform. OWASP Web Application Security Series: Broken access mitigation Cryptographic failures Injection mitigation Insecure design mitigation Security misconfiguration prevention Vulnerable and outdated components Identification failures prevention Software failures mitigation Security logging issues prevention SSRF Mitigation
