Python script to get the SSL profile of a VIP
Hello guys I am creating an SSL automation and I am trying to get the ssl profile from inputted VIP.. I am using F5 rest api and I am not seeing much differences on the contents when I use this url url = f"https://{f5_hostname}/mgmt/tm/ltm/virtual/~Common~{vip_name}" and filter using profilesReference it gave me all profiles sample below. From below contents, I dont know how to filter further to get the sslprofile as you see almost all of them has the same content, I cannot differentiate the ssl profile from others. any other way how to get the sslprofile from a VIP using python script? { "kind": "tm:ltm:virtual:profiles:profilesstate", "name": "myssslprofile.com", ->>>> this is the ssl profile "partition": "Common", "fullPath": "/Common/myssslprofile.com", "generation": 1, "selfLink": "https://localhost/mgmt/tm/ltm/virtual/exampleVIP.com/profiles/~Common~myssslprofile.com?ver=16.x.x.x", "context": "clientside" }, { "kind": "tm:ltm:virtual:profiles:profilesstate", "name": "tcp-lan-optimized", "partition": "Common", "fullPath": "/Common/tcp-lan-optimized", "generation": 1, "selfLink": "https://localhost/mgmt/tm/ltm/virtual/exampleVIP.com/profiles/~Common~tcp-lan-optimized?ver=16.x.x.x", "context": "serverside" }, { "kind": "tm:ltm:virtual:profiles:profilesstate", "name": "tcp-wan-optimized", "partition": "Common", "fullPath": "/Common/tcp-wan-optimized", "generation": 1, "selfLink": "https://localhost/mgmt/tm/ltm/virtual/exampleVIP.com/profiles/~Common~tcp-wan-optimized?ver=16.x.x.x", "context": "clientside" }, { "kind": "tm:ltm:virtual:profiles:profilesstate", "name": "anotheprofile", "partition": "Common", "fullPath": "/Common/anotheprofile", "generation": 1, "selfLink": "https://localhost/mgmt/tm/ltm/virtual/exampleVIP.com/profiles/~Common~anotheprofile?ver=16.x.x.x", "context": "serverside" },
Microsoft 365 IP Steering python script
Hello! Hola! I have created a small and rudimentary script that generates a datagroup with MS 365 IPv4 and v6 addresses to be used by an iRule or policy. There are other scripts that solve this same issue but either they were: based on iRulesLX, which forces you to enable iRuleLX only for this, and made me run into issues when upgrading (memory table got filled with nonsense) based on the XML version of the list, which MS changed to a JSON file. This script is a super simple bash script that calls another super simple python file, and a couple of helper files. The biggest To Do are: Add a more secure approach to password usage. Right now, it is stored in a parameters file locked away with permissions. There should be a better way. Add support for URLs. You can find the contents here:https://github.com/teoiovine-novared/fetch-office365/tree/main I appreciate advice, (constructive) criticism and questions all the same! Thank you for your time.VIPTest: Rapid Application Testing for F5 Environments
VIPTest is a Python-based tool for efficiently testing multiple URLs in F5 environments, allowing quick assessment of application behavior before and after configuration changes. It supports concurrent processing, handles various URL formats, and provides detailed reports on HTTP responses, TLS versions, and connectivity status, making it useful for migrations and routine maintenance.Demystifying iControl REST Part 7 - Understanding Transactions
iControl REST. It’s iControl SOAP’s baby, brother, introduced back in TMOS version 11.4 as an early access feature but released fully in version 11.5. Several articles on basic usage have been written about the rest interface so the intent here isn’t basic use, but rather to demystify some of the finer details of using the API. A few months ago, a question in Q&A from community member spirrello asking how to update a tcp profile on a virtual. He was using bigsuds, the python wrapper for the soap interface. For the rest interface on this particular object, this is easy; just use the put method and supply the payload mapping the updated profile. But for soap, this requires a transaction. There are some changes to BIG-IP via the rest interface, however, like updating an ssl cert or key, that likewise will require a transaction to accomplish. In this article, I’ll show you how to use transactions with the rest interface. The Fine Print From the iControl REST user guide, the life cycle of a transaction progresses through three phases: Creation - This phase occurs when the transaction is created using a POST command. Modification - This phase occurs when commands are added to the transaction, or changes are made to the sequence of commands in the transaction. Commit - This phase occurs when iControl REST runs the transaction. To create a transaction, post to /tm/transaction POST https://192.168.25.42/mgmt/tm/transaction {} Response: { "transId":1389812351, "state":"STARTED", "timeoutSeconds":30, "kind":"tm:transactionstate", "selfLink":"https://localhost/mgmt/tm/transaction/1389812351?ver=11.5.0" } Note the transId, the state, and the timeoutSeconds. You'll need the transId to add or re-sequence commands within the transaction, and the transaction will expire after 30 seconds if no commands are added. You can list all transactions, or the details of a specific transaction with a get request. GET https://192.168.25.42/mgmt/tm/transaction GET https://192.168.25.42/mgmt/tm/transaction/transId To add a command to the transaction, you use the normal method uris, but include the X-F5-REST-Coordination-Id header. This example creates a pool with a single member. POST https://192.168.25.42/mgmt/tm/ltm/pool X-F5-REST-Coordination-Id:1389812351 { "name":"tcb-xact-pool", "members": [ {"name":"192.168.25.32:80","description":"First pool for transactions"} ] } Not a great example because there is no need for a transaction here, but we'll roll with it! There are several other option methods for interrogating the transaction itself, see the user guide for details. Now we can commit the transaction. To do that, you reference the transaction id in the URI, remove the X-F5-REST-Coordination-Id header and use the patch method with payload key/value state: VALIDATING . PATCH https://localhost/mgmt/tm/transaction/1389812351 { "state":"VALIDATING" } That's all there is to it! Now that you've seen the nitty gritty details, let's take a look at some code samples. Roll Your Own In this example, I am needing to update and ssl key and certificate. If you try to update the cert or the key, it will complain that they do not match, so you need to update both at the same time. Assuming you are writing all your code from scratch, this is all it takes in python. Note on line 21 I post with an empty payload, and then on line 23, I add the header with the transaction id. I make my modifications and then in line 31, I remove the header, and finally on line 32, I patch to the transaction id with the appropriate payload. import json import requests btx = requests.session() btx.auth = (f5_user, f5_password) btx.verify = False btx.headers.update({'Content-Type':'application/json'}) urlb = 'https://{0}/mgmt/tm'.format(f5_host) domain = 'mydomain.local_sslobj' chain = 'mychain_sslobj try: key = btx.get('{0}/sys/file/ssl-key/~Common~{1}'.format(urlb, domain)) cert = btx.get('{0}/sys/file/ssl-cert/~Common~{1}'.format(urlb, domain)) chain = btx.get('{0}/sys/file/ssl-cert/~Common~{1}'.format(urlb, 'chain')) if (key.status_code == 200) and (cert.status_code == 200) and (chain.status_code == 200): # use a transaction txid = btx.post('{0}/transaction'.format(urlb), json.dumps({})).json()['transId'] # set the X-F5-REST-Coordination-Id header with the transaction id btx.headers.update({'X-F5-REST-Coordination-Id': txid}) # make modifications modkey = btx.put('{0}/sys/file/ssl-key/~Common~{1}'.format(urlb, domain), json.dumps(keyparams)) modcert = btx.put('{0}/sys/file/ssl-cert/~Common~{1}'.format(urlb, domain), json.dumps(certparams)) modchain = btx.put('{0}/sys/file/ssl-cert/~Common~{1}'.format(urlb, 'le-chain'), json.dumps(chainparams)) # remove header and patch to commit the transaction del btx.headers['X-F5-REST-Coordination-Id'] cresult = btx.patch('{0}/transaction/{1}'.format(urlb, txid), json.dumps({'state':'VALIDATING'})).json() A Little Help from a Friend The f5-common-python library was released a few months ago to relieve you of a lot of the busy work with building requests. This is great, especially for transactions. To simplify the above code just to the transaction steps, consider: # use a transaction txid = btx.post('{0}/transaction'.format(urlb), json.dumps({})).json()['transId'] # set the X-F5-REST-Coordination-Id header with the transaction id btx.headers.update({'X-F5-REST-Coordination-Id': txid}) # do stuff here # remove header and patch to commit the transaction del btx.headers['X-F5-REST-Coordination-Id'] cresult = btx.patch('{0}/transaction/{1}'.format(urlb, txid), json.dumps({'state':'VALIDATING'})).json() With the library, it's simplified to: tx = b.tm.transactions.transaction with TransactionContextManager(tx) as api: # do stuff here api.do_stuff Yep, it's that simple. So if you haven't checked out the f5-common-python library, I highly suggest you do! I'll be writing about how to get started using it next week, and perhaps a follow up on how to contribute to it as well, so stay tuned!BIG-IP Next Central Manager API with Python
I've been working with the BIG-IP Next API with curl on the command line and with the Postman GUI app as well. Both useful as I am getting comfortable with the API, but not my favorite tools in the toolbox, which is python. In this episode of DevCentral Connects, I'll share the early stages of a tool I'm building for working with BIG-IP Next in python and walk through some tasks with the BIG-IP Next API.Demystifying iControl REST Part 6: Token-Based Authentication
iControl REST. It’s iControl SOAP’s baby, brother, introduced back in TMOS version 11.4 as an early access feature but released fully in version 11.5. Several articles on basic usage have been written on iControl REST so the intent here isn’t basic use, but rather to demystify some of the finer details of using the API. This article will cover the details on how to retrieve and use an authentication token from the BIG-IP using iControl REST and the python programming language. This token is used in place of basic authentication on API calls, which is a requirement for external authentication. Note that for configuration changes, version 12.0 or higher is required as earlier versions will trigger an un-authorized error. The tacacs config in this article is dependent on a version that I am no longer able to get installed on a modern linux flavor. Instead, try this Dockerized tacacs+ server for your testing. The Fine Print The details of the token provider are here in the wiki. We’ll focus on a provider not listed there: tmos. This provider instructs the API interface to use the provider that is configured in tmos. For this article, I’ve configured a tacacs server and the BIG-IP with custom remote roles as shown below to show BIG-IP version 12’s iControl REST support for remote authentication and authorization. Details for how this configuration works can be found in the tacacs+ article I wrote a while back. BIG-IP tacacs+ configuration auth remote-role { role-info { adm { attribute F5-LTM-User-Info-1=adm console %F5-LTM-User-Console line-order 1 role %F5-LTM-User-Role user-partition %F5-LTM-User-Partition } mgr { attribute F5-LTM-User-Info-1=mgr console %F5-LTM-User-Console line-order 2 role %F5-LTM-User-Role user-partition %F5-LTM-User-Partition } } } auth remote-user { } auth source { type tacacs } auth tacacs system-auth { debug enabled protocol ip secret $M$Zq$T2SNeIqxi29CAfShLLqw8Q== servers { 172.16.44.20 } service ppp } Tacacs+ Server configuration id = tac_plus { debug = PACKET AUTHEN AUTHOR access log = /var/log/access.log accounting log = /var/log/acct.log host = world { address = ::/0 prompt = "\nAuthorized Access Only!\nTACACS+ Login\n" key = devcentral } group = adm { service = ppp { protocol = ip { set F5-LTM-User-Info-1 = adm set F5-LTM-User-Console = 1 set F5-LTM-User-Role = 0 set F5-LTM-User-Partition = all } } } group = mgr { service = ppp { protocol = ip { set F5-LTM-User-Info-1 = mgr set F5-LTM-User-Console = 1 set F5-LTM-User-Role = 100 set F5-LTM-User-Partition = all } } } user = user_admin { password = clear letmein00 member = adm } user = user_mgr { password = clear letmein00 member = mgr } } Basic Requirements Before we look at code, however, let’s take a look at the json payload requirements, followed by response data from a query using Chrome’s Advanced REST Client plugin. First, since we are sending json payload, we need to add the Content-Type: application/json header to the query. The payload we are sending with the post looks like this: { "username": "remote_auth_user", "password": "remote_auth_password", "loginProviderName": "tmos" } You submit the same remote authentication credentials in the initial basic authentication as well, no need to have access to the default admin account credentials. A successful query for a token returns data like this: { username: "user_admin" loginReference: { link: "https://localhost/mgmt/cm/system/authn/providers/tmos/1f44a60e-11a7-3c51-a49f-82983026b41b/login" }- token: { uuid: "4d1bd79f-dca7-406b-8627-3ad262628f31" name: "5C0F982A0BF37CBE5DE2CB8313102A494A4759E5704371B77D7E35ADBE4AAC33184EB3C5117D94FAFA054B7DB7F02539F6550F8D4FA25C4BFF1145287E93F70D" token: "5C0F982A0BF37CBE5DE2CB8313102A494A4759E5704371B77D7E35ADBE4AAC33184EB3C5117D94FAFA054B7DB7F02539F6550F8D4FA25C4BFF1145287E93F70D" userName: "user_admin" user: { link: "https://localhost/mgmt/cm/system/authn/providers/tmos/1f44a60e-11a7-3c51-a49f-82983026b41b/users/34ba3932-bfa3-4738-9d55-c81a1c783619" }- groupReferences: [1] 0: { link: "https://localhost/mgmt/cm/system/authn/providers/tmos/1f44a60e-11a7-3c51-a49f-82983026b41b/user-groups/21232f29-7a57-35a7-8389-4a0e4a801fc3" }- - timeout: 1200 startTime: "2015-11-17T19:38:50.415-0800" address: "172.16.44.1" partition: "[All]" generation: 1 lastUpdateMicros: 1447817930414518 expirationMicros: 1447819130415000 kind: "shared:authz:tokens:authtokenitemstate" selfLink: "https://localhost/mgmt/shared/authz/tokens/4d1bd79f-dca7-406b-8627-3ad262628f31" }- generation: 0 lastUpdateMicros: 0 } Among many other fields, you can see the token field with a very long hexadecimal token. That’s what we need to authenticate future API calls. Requesting the token programmatically In order to request the token, you first have to supply basic auth credentials like normal. This is currently required to access the /mgmt/shared/authn/login API location. The basic workflow is as follows (with line numbers from the code below in parentheses): Make a POST request to BIG-IP with basic authentication header and json payload with username, password, and the login provider (9-16, 41-47) Remove the basic authentication (49) Add the token from the post response to the X-F5-Auth-Token header (50) Continue further requests like normal. In this example, we’ll create a pool to verify read/write privileges. (1-6, 52-53) And here’s the code (in python) to make that happen: def create_pool(bigip, url, pool): payload = {} payload['name'] = pool pool_config = bigip.post(url, json.dumps(payload)).json() return pool_config def get_token(bigip, url, creds): payload = {} payload['username'] = creds[0] payload['password'] = creds[1] payload['loginProviderName'] = 'tmos' token = bigip.post(url, json.dumps(payload)).json()['token']['token'] return token if __name__ == "__main__": import os, requests, json, argparse, getpass requests.packages.urllib3.disable_warnings() parser = argparse.ArgumentParser(description='Remote Authentication Test - Create Pool') parser.add_argument("host", help='BIG-IP IP or Hostname', ) parser.add_argument("username", help='BIG-IP Username') parser.add_argument("poolname", help='Key/Cert file names (include the path.)') args = vars(parser.parse_args()) hostname = args['host'] username = args['username'] poolname = args['poolname'] print "%s, enter your password: " % args['username'], password = getpass.getpass() url_base = 'https://%s/mgmt' % hostname url_auth = '%s/shared/authn/login' % url_base url_pool = '%s/tm/ltm/pool' % url_base b = requests.session() b.headers.update({'Content-Type':'application/json'}) b.auth = (username, password) b.verify = False token = get_token(b, url_auth, (username, password)) print '\nToken: %s\n' % token b.auth = None b.headers.update({'X-F5-Auth-Token': token}) response = create_pool(b, url_pool, poolname) print '\nNew Pool: %s\n' % response Running this script from the command line, we get the following response: FLD-ML-RAHM:scripts rahm$ python remoteauth.py 172.16.44.15 user_admin myNewestPool1 Password: user_admin, enter your password: Token: 2C61FE257C7A8B6E49C74864240E8C3D3592FDE9DA3007618CE11915F1183BF9FBAF00D09F61DE15FCE9CAB2DC2ACC165CBA3721362014807A9BF4DEA90BB09F New Pool: {u'generation': 453, u'minActiveMembers': 0, u'ipTosToServer': u'pass-through', u'loadBalancingMode': u'round-robin', u'allowNat': u'yes', u'queueDepthLimit': 0, u'membersReference': {u'isSubcollection': True, u'link': u'https://localhost/mgmt/tm/ltm/pool/~Common~myNewestPool1/members?ver=12.0.0'}, u'minUpMembers': 0, u'slowRampTime': 10, u'minUpMembersAction': u'failover', u'minUpMembersChecking': u'disabled', u'queueTimeLimit': 0, u'linkQosToServer': u'pass-through', u'queueOnConnectionLimit': u'disabled', u'fullPath': u'myNewestPool1', u'kind': u'tm:ltm:pool:poolstate', u'name': u'myNewestPool1', u'allowSnat': u'yes', u'ipTosToClient': u'pass-through', u'reselectTries': 0, u'selfLink': u'https://localhost/mgmt/tm/ltm/pool/myNewestPool1?ver=12.0.0', u'serviceDownAction': u'none', u'ignorePersistedWeight': u'disabled', u'linkQosToClient': u'pass-through'} You can test this out in the Chrome Advanced Rest Client plugin, or from the command line with curl or any other language supporting REST clients as well, I just use python for the examples well, because I like it. I hope you all are digging into iControl REST! What questions do you have? What else would you like clarity on? Drop a comment below.Parsing F5 BIG-IP LTM DNS profile statistics and extracting values with Python
Introduction Hello there! Arvin here from the F5 SIRT. A little while ago, I published F5BIG-IP Advanced Firewall Manager (AFM) DNS NXDOMAIN Query Attack Type Walkthroughpart one and two, where I went through the process of reviewing BIG-IP LTM DNS profile statistics and used it to set BIG-IP AFM DNS NXDOMAIN Query attack type detection and mitigation thresholds with the goal of mitigating DNS NXDOMAIN Floods. In this article, I continue to look atBIG-IP LTM DNS profile statistics, find ways of parsing it and to extract specific values of interest through Python. Python for Network Engineers Python has emerged as a go-to language for network engineers, providing a powerful and accessible toolset for managing and automating network tasks. Known for its simplicity and readability, Python enables network engineers to script routine operations, automate repetitive tasks, and interact with network devices through APIs. With extensive libraries and frameworks tailored to networking, Python empowers engineers to streamline configurations, troubleshoot issues, and enhance network efficiency. Its versatility makes it an invaluable asset for network automation, allowing engineers to adapt to evolving network requirements and efficiently manage complex infrastructures. Whether you're retrieving data, configuring devices, or optimizing network performance, Python simplifies the process for network engineers, making it an essential skill in the modern networking landscape. The Tools ChatGPT3.5 The "Python for Network Engineers" intro came from ChatGPT3.5 [:)]. Throughout this article, the python coding "bumps" avoidance and approaches came from ChatGPT3.5. Instead of googling, I asked ChatGPT "a lot" so I could get the python scripts to get the output I wanted. https://chat.openai.com/ Visual Studio Code UsingVisual Studio Code (VSCode) to build the scripts was very helpful, especially the tooltip / hints which tells me and help make sense of the available options for the modules used and describing the python data structures. Python 3.10 (From ChatGPT)Python 3.10, the latest version of the Python programming language, brings forth new features and optimizations that enhance the language's power and simplicity. With Python's commitment to readability and ease of use, version 3.10 introduces structural pattern matching, allowing developers to express complex logic more concisely. Other improvements include precise types, performance enhancements, and updates to syntax for cleaner code. Python 3.10 continues to be a versatile and accessible language, serving diverse needs from web development to data science and automation. Its vibrant community and extensive ecosystem of libraries make Python 3.10 a top choice for developers seeking both efficiency and clarity in their code. Python Script - extract DNS A requests value from LTM DNS profile statistics iControl REST output This python script will extract DNS A requests value from LTM DNS profile statistics iControl REST output. Python has many modules that can be used to simplify tasks. iControl REST output is in json format, so as expected, I used the json module. I wanted to format the output data in csv format so the extracted data can later be used in other tools that consume csv formatted data, thus, I used the csv module. I also used the os, time/datetime and tabulate modules for working with the filesystem (I used a Windows machine to run Python and VSCode) to write csv files. Create variables with date and time information that will be used in formatting the csv file name, keep track of the "A record requests" value at script execution, and present a tabulated output of the captured time and data when the script is executed. I also used BIGREST module to query/retrieve the "show ltm dns profile <DNS profile> statistics" instead of getting the output from iControl REST request sent through other methods. https://bigrest.readthedocs.io/introduction.html https://bigrest.readthedocs.io/bigip_show.html Here is the sample script output Here is the sample CSV-formatted data in a csv file with timestamp of the script run I created a github repository for the Python script and its sample script output and csv data see https://github.com/arvfopa/scripts/tree/main https://github.com/arvfopa/scripts/blob/main/extractAreq- Python Script "extractAreq" https://github.com/arvfopa/scripts/blob/main/extractAreq_output- "extractAreq" output Bumps along the way BIGREST module I initially encountered an error 'certificate verify failed: self signed certificate' when provided only the IP address and credentials used in the BIGIP class of the bigrest.bigip python module raise SSLError(e, request=request) requests.exceptions.SSLError: HTTPSConnectionPool(host='IP address', port=443): Max retries exceeded with url: /mgmt/shared/echo-query (Caused by SSLError(SSLCertVerificationError(1, '[SSL: CERTIFICATE_VERIFY_FAILED] certificate verify failed: self signed certificate (_ssl.c:1007)'))) This is fixed by setting "session_verify" argument of the BIGIP class to "false" to disables SSL certificate validation device = BIGIP("<IP address>", "<username>", "<password>" , session_verify=False) https://bigrest.readthedocs.io/utils.html I also received this error "TypeError: Object of type RESTObject is not JSON serializable" raise TypeError(f'Object of type {o.__class__.__name__} ' TypeError: Object of type RESTObject is not JSON serializable I reread the BIGREST documentation and found that the output is a python dictionary and can is printed in json format.I rechecked the script and removed the json related syntax and module, and the script runs fine and still gets the same output. I updated the script on github with the simplified changes. https://bigrest.readthedocs.io/restobject.html Here's a sample of the RESTObject properties dictionary values. Plenty of data can be extracted. Example, "clientside.pktsIn" value, a virtual server statistic, can be observed and should detection and mitigation thresholds for AFM, say, UDP protocol DoS attack type, need to be set. This value can be monitored over time to understand how many packets a virtual server receives. ============== {'clientside.bitsIn': {'value': 0}, 'clientside.bitsOut': {'value': 0}, 'clientside.curConns': {'value': 0}, 'clientside.evictedConns': {'value': 0}, 'clientside.maxConns': {'value': 0}, 'clientside.pktsIn': {'value': 0}, 'clientside.pktsOut': {'value': 0}, 'clientside.slowKilled': {'value': 0}, 'clientside.totConns': {'value': 0}, 'cmpEnableMode': {'description': 'all-cpus'}, 'cmpEnabled': {'description': 'enabled'}, 'csMaxConnDur': {'value': 0}, 'csMeanConnDur': {'value': 0}, 'csMinConnDur': {'value': 0}, 'destination': {'description': '10.73.125.137:53'}, 'ephemeral.bitsIn': {'value': 0}, 'ephemeral.bitsOut': {'value': 0}, 'ephemeral.curConns': {'value': 0}, 'ephemeral.evictedConns': {'value': 0}, ============== CSV filename issue I encountered thiserror,"OSError: [Errno 22] Invalid argument: 'dns_stats_2023-12-07_18:01:11.csv". This is related to writing of the output csv file. I asked ChatGPT what this was about andwas providedwith thisanswer. ======================= The error you're encountering, "[Errno 22] Invalid argument," typically suggests an issue with the filename or file path. In this case, it seems to be related to the colon (':') character in the filename. In some operating systems (like Windows), certain characters are not allowed in filenames, and ":" is one of them. Since you're including a timestamp in the filename, it's common to replace such characters with alternatives. You can modify the timestamp format to use underscores or hyphens instead of colons. ==================== The timestamp variable in the script stores the value of the formatted timestamp that will be used in the filename. It initially used a colon (:) as the hour/min/sec separator. It was changed to dash (-) so it would not encounter this error. timestamp = datetime.now().strftime("%Y-%m-%d_%H-%M-%S") Checking the file csv file if it exists The function "write_to_csv" writes the time of collection (formatted_date) andextracted value of DNS A requests count (AReqsvalue). It is called every 10 seconds [time.sleep(10)] for a minute [end_time = time.time() + 60] and writes the output to a file in csv format. The "tabulate" function formats the output of the script. Getting the arrangement of the execution wrong would result in unexpected output. The "file_exists" check to write the "headers" was added to make sure that the "headers" are only written once. "write_to_csv" function ======================== def write_to_csv(formatted_date, AReqsvalue): current_datetime = datetime.now() formatted_date = current_datetime.strftime("%Y-%m-%d %H:%M:%S") csv_filename = f"dns_stats_{timestamp}.csv" headers = ["Date", "DNS A requests"] stats = [[formatted_date, AReqsvalue]] file_exists = os.path.exists(csv_filename) print(tabulate(stats, headers, tablefmt="fancy_grid")) with open(csv_filename, mode='a', newline='') as file: writer = csv.writer(file) if not file_exists: writer.writerow(headers) writer.writerows(stats) end_time = time.time() + 60 while time.time() < end_time: write_to_csv(formatted_date, AReqsvalue) time.sleep(10) ========================== Using ChatGPT In building this script, I usedChatGPT "a lot" and it helped to provide make more sense of the module options, errors and sample scripts. It has been a helpful tool. It tracks your conversation/questions to it and kind of understands the context/topic. "ChatGPT can make mistakes. Consider checking important information." is written at the bottom of the page. The data I used in this article are data from a lab environment.That said, when using public AI/ML systems, we should ensure we do not send any sensitive, proprietary information. Organizations have rolled out their own privacy policies when using AI/ML systems, be sure to follow your own organization's policies. Conclusion Using python to parse and extract values of interest from LTM profile statistics offers flexibility and hopefully simplifying observing and recording these data for further use. In particular, setting values for BIG-IP AFM DoS Detection and Mitigation thresholds will be easier if such data has been observed as it, in my opinion, is the "pulse" of the traffic the BIG-IP processes. As noted in the sample json data output, we can see many statistics that can be reviewed and observed to make configuration changes relevant, for example, mitigating a connection spike by setting a VS connection/rate limit. We can look at the "Conns" values and use the observed values to set a connection limit. Example: 'clientside.curConns': {'value': 0}, 'clientside.evictedConns': {'value': 0}, 'clientside.maxConns': {'value': 0}, 'clientside.totConns':{'value': 0} That's it for now. I hope this article has been educational. The F5 SIRT createssecurity-related content posted here in DevCentral, sharing the team's security mindset and knowledge. Feel free to view the articles that are tagged withthe following: F5 SIRT series-F5SIRT-this-week-in-security TWISiControl REST Python Requests module
While iControl REST is great and pretty robust given how much we use it. But I come to the forum today to see if anyone has any experience with the Python requests module and the underlying urllib3 module. When I do have problems with iControl its often with things like the following: Here I've increased the timeout to 5.0 seconds but still get read timeouts. HTTPSConnectionPool(host='redacted', port=443): Read timed out. (read timeout=5.0) I also often see this message and, no I don't have a proxy in front of the F5. However, I know the the F5 proxies the REST call (Caused by ProxyError('Cannot connect to proxy.', OSError('Tunnel connection failed: 503 Service Unavailable', Thanks!
