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In this post I will show you some of my research trying to build existing Signals Corps products using ChatGPT.
Many of our products were created pre-2020, and perhaps (to be determined), the process of building them might have been much easier using GPT. I already know from previous posts, GPT can write code.
I wanted to explore this further.
At the start of this year I described how cve2stix was built.
A large part of the cve2stix functionality translates data returned from APIs and dictionaries to STIX 2.1 Object.
Based on these previous posts, building the logic to download and convert the data used by cve2stix seemed to be a trivial task for GPT.
With this in mind, I started by trying to achieve the CPE to STIX 2.1 conversion (a key part of cve2stix) using a small sample of three products from the NVD API;
GET https://services.nvd.nist.gov/rest/json/cpes/2.0/?lastModStartDate=2021-08-04T13:00:00.000%2B01:00&lastModEndDate=2021-10-22T13:36:00.000%2B01:00&cpeMatchString=cpe:2.3:a:apple
Response:
{
"resultsPerPage": 3,
"startIndex": 0,
"totalResults": 3,
"format": "NVD_CPE",
"version": "2.0",
"timestamp": "2023-01-06T15:46:40.793",
"products": [
{
"cpe": {
"deprecated": false,
"cpeName": "cpe:2.3:a:apple:safari:14.1.2:*:*:*:*:*:*:*",
"cpeNameId": "78DEE287-2542-4591-99FC-E961C3DBE74E",
"lastModified": "2021-09-17T18:29:54.370",
"created": "2021-09-14T14:43:00.740",
"titles": [
{
"title": "Apple Safari 14.1.2",
"lang": "en"
}
],
"refs": [
{
"ref": "https://support.apple.com/en-us/HT212606",
"type": "Change Log"
}
]
}
},
{
"cpe": {
"deprecated": false,
"cpeName": "cpe:2.3:a:apple:boot_camp:6.1.14:*:*:*:*:*:*:*",
"cpeNameId": "E5428D10-40C8-4C2A-BBEB-9936654714FF",
"lastModified": "2021-09-19T01:27:12.450",
"created": "2021-09-16T14:42:09.773",
"titles": [
{
"title": "Apple Boot Camp 6.1.14",
"lang": "en"
}
],
"refs": [
{
"ref": "https://support.apple.com/en-us/HT212517",
"type": "Product"
}
]
}
},
{
"cpe": {
"deprecated": false,
"cpeName": "cpe:2.3:a:apple:boot_camp:-:*:*:*:*:*:*:*",
"cpeNameId": "0AAAB8F0-3F20-4DAB-B7D0-6AE256E4B64A",
"lastModified": "2021-09-22T16:55:23.163",
"created": "2021-09-21T13:32:21.907",
"titles": [
{
"title": "Apple Boot Camp",
"lang": "en"
}
],
"refs": [
{
"ref": "https://support.apple.com/boot-camp",
"type": "Product"
}
]
}
}
]
}
In this example there are three CPE’s which are converted to STIX 2.1 Software Objects in cve2stix. Lets try it with ChatGPT after feeding in the JSON response.
Input:
Please convert each CPE in products.cpe object in from the previous prompt to a STIX 2.1 Software object using the following logic;
{
"type": "software",
"spec_version": "2.1",
"id": "software--<A>",
"name": "<B>",
"cpe": "<C>",
"version": "<D>",
"vendor": "<E>",
"object_marking_refs": [
"marking-definition--613f2e26-407d-48c7-9eca-b8e91df99dc9"
],
"extensions": {
"extension-definition--6c453e0f-9895-498f-a273-2e2dda473377": {
"extension_type": "property-extension",
"<F>"
}
}
}
Where:
<A>: is a UUIDv5 generated using thecpevalue using the STIX2 Python library (https://pypi.org/project/stix2/)<B>: is theproducts.cpe.titles.titlevalue in the NVD API response. If more than one value exists, use whereproducts.cpe.titles.langisen.<C>: is theproducts.cpe.cpeNamevalue in the response<D>: is found in theproducts.cpe.cpeNamebetween the fifth and sixth:characters. For example, in thisproducts.cpe.cpeNameiscpe:2.3:a:apple:boot_camp:6.1.14:*:*:*:*:*:*:*,<D>is6.1.14<E>: is found in theproducts.cpe.cpeNamebetween the third and fourth:characters. For example, in thisproducts.cpe.cpeNameiscpe:2.3:a:apple:boot_camp:6.1.14:*:*:*:*:*:*:*,<E>isapple<F>: is the entire value forproducts.cpein the NVD API payload
Please print the STIX 2.1 Software SCOs in your response.
Output:
I won’t post the entire JSON payload here, see the object graph below for full JSON.
Review:
Perfect!
Lets try it with CVE’s. I’ll use the following example data;
GET https://services.nvd.nist.gov/rest/json/cves/2.0/?cveId=CVE-2019-1010218
Which prints all the information about the CVE;
{
"resultsPerPage": 1,
"startIndex": 0,
"totalResults": 1,
"format": "NVD_CVE",
"version": "2.0",
"timestamp": "2023-01-08T14:10:27.753",
"vulnerabilities": [
{
"cve": {
"id": "CVE-2019-1010218",
"sourceIdentifier": "[email protected]",
"published": "2019-07-22T18:15:10.917",
"lastModified": "2020-09-30T13:40:18.163",
"vulnStatus": "Analyzed",
"descriptions": [
{
"lang": "en",
"value": "Cherokee Webserver Latest Cherokee Web server Upto Version 1.2.103 (Current stable) is affected by: Buffer Overflow - CWE-120. The impact is: Crash. The component is: Main cherokee command. The attack vector is: Overwrite argv[0] to an insane length with execl. The fixed version is: There's no fix yet."
},
{
"lang": "es",
"value": "El servidor web de Cherokee más reciente de Cherokee Webserver Hasta Versión 1.2.103 (estable actual) está afectado por: Desbordamiento de Búfer - CWE-120. El impacto es: Bloqueo. El componente es: Comando cherokee principal. El vector de ataque es: Sobrescribir argv[0] en una longitud no sana con execl. La versión corregida es: no hay ninguna solución aún."
}
],
"metrics": {
"cvssMetricV31": [
{
"source": "[email protected]",
"type": "Primary",
"cvssData": {
"version": "3.1",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H",
"attackVector": "NETWORK",
"attackComplexity": "LOW",
"privilegesRequired": "NONE",
"userInteraction": "NONE",
"scope": "UNCHANGED",
"confidentialityImpact": "NONE",
"integrityImpact": "NONE",
"availabilityImpact": "HIGH",
"baseScore": 7.5,
"baseSeverity": "HIGH"
},
"exploitabilityScore": 3.9,
"impactScore": 3.6
}
],
"cvssMetricV2": [
{
"source": "[email protected]",
"type": "Primary",
"cvssData": {
"version": "2.0",
"vectorString": "AV:N/AC:L/Au:N/C:N/I:N/A:P",
"accessVector": "NETWORK",
"accessComplexity": "LOW",
"authentication": "NONE",
"confidentialityImpact": "NONE",
"integrityImpact": "NONE",
"availabilityImpact": "PARTIAL",
"baseScore": 5.0
},
"baseSeverity": "MEDIUM",
"exploitabilityScore": 10.0,
"impactScore": 2.9,
"acInsufInfo": false,
"obtainAllPrivilege": false,
"obtainUserPrivilege": false,
"obtainOtherPrivilege": false,
"userInteractionRequired": false
}
]
},
"weaknesses": [
{
"source": "[email protected]",
"type": "Primary",
"description": [
{
"lang": "en",
"value": "CWE-787"
}
]
},
{
"source": "[email protected]",
"type": "Secondary",
"description": [
{
"lang": "en",
"value": "CWE-120"
}
]
}
],
"configurations": [
{
"nodes": [
{
"operator": "OR",
"negate": false,
"cpeMatch": [
{
"vulnerable": true,
"criteria": "cpe:2.3:a:cherokee-project:cherokee_web_server:*:*:*:*:*:*:*:*",
"versionEndIncluding": "1.2.103",
"matchCriteriaId": "DCE1E311-F9E5-4752-9F51-D5DA78B7BBFA"
}
]
}
]
}
],
"references": [
{
"url": "https://i.imgur.com/PWCCyir.png",
"source": "[email protected]",
"tags": [
"Exploit",
"Third Party Advisory"
]
}
]
}
}
]
}
Like with the CPE, I will first feed this JSON response from NVD covering a single CVE and then ask it to convert it to a STIX 2.1 Vulnerability object.
Input:
Please convert the CVE represented in the previous prompt to a STIX 2.1 Vulnerability object using the following logic;
{
"type": "vulnerability",
"spec_version": "2.1",
"id": "vulnerability--<A>",
"created": "<B>",
"modified": "<C>",
"name": "CVE: <D>",
"description": "<E>",
"external_references": [
{
"source_name": "cve",
"external_id": "<D>",
"url": "https://nvd.nist.gov/vuln/detail/<D>"
},
{
"source_name": "cwe",
"external_id": "<F>",
"url": "https://cwe.mitre.org/data/definitions/<F>"
},
{
"source_name": "<G1>",
"url": "<G2>",
"description": "[<G3>]"
}
],
"object_marking_refs": [
"marking-definition--613f2e26-407d-48c7-9eca-b8e91df99dc9"
],
"labels": [
"cvssv3ExploitabilityScore: <H>",
"cvssv3ImpactScore: <I>"
],
"extensions": {
"extension-definition--b2b5f2cd-49e6-4091-a0e0-c0bb71543e23": {
"extension_type": "property-extension",
"<J>"
}
}
}
Where;
<A>: is a UUIDv4 generated using the STIX2 Python library (https://pypi.org/project/stix2/)<B>: is thevulnerabilities.cve.publishedvalue in the NVD API response.<C>: is thevulnerabilities.cve.lastModifiedvalue in the NVD API response.<D>: is thevulnerabilities.cve.idvalue in the NVD API response.<E>: is thevulnerabilities.cve.descriptions.description_data.value. If more than one value exists, use wherevulnerabilities.cve.descriptions.description_data.langisen.<F>: is thevulnerabilities.cve.weaknesses.description.valuein the NVD API response. Note, more than one value might exist. Where more than one value exists, please create a seperate object for each.<G1>: is thevulnerabilities.cve.references.sourcein the NVD API response. Note, more than one value might exist. Where more than one value exists, please create a seperate object for each.<G2>: is thevulnerabilities.cve.references.urlin the NVD API response for<G1><G3>: is thevulnerabilities.cve.references.tagin the NVD API response for<G1><H>: is thevulnerabilities.cve.metrics.cvssMetricV31.exploitabilityScorein the NVD API response.<I>: is thevulnerabilities.cve.metrics.cvssMetricV31.impactScorein the NVD API response.<J>: is the entire value forvulnerabilities.cvein the NVD API payload
Please print the STIX 2.1 Vulnerability in your response.
Output:
Review:
Again, a perfect output based on detailed instructions.
Now that GPT understands how to extract individual objects, it now needs to be instructed how to do it programmatically.
I know from the lasts posts that GPT can write code (to generate STIX 2.1 objects), but that was fairly simplistic, lets see how it deals with a slightly more complex requirement.
First, lets start with a basic script that takes a payload from the NVD CPE API and converts the CPE records to STIX 2.1 Software Objects.
Input:
Can you please write a Python 3 script that takes the JSON file (in the format from the NVD API shown earlier) as a command line input and converts each CPE entry to STIX 2.1 SOftware objects using the same logic as before?
Output:
Certainly! Here’s an example script that reads in a JSON file containing CPE records in the same format as the NVD API and converts them to STIX 2.1 Software objects:
To run the script, you would provide the path to the input JSON file as a command line argument:
python3 convert_cpes_to_stix_from_file.py input.json
Note that the script assumes that the input JSON file contains a top-level products key with an array of CPE records, just like the response from the NVD API. If your JSON file has a different structure, you may need to modify the script accordingly.
Review:
To test the output, I will grab a sample JSON payload from my browser and save it as test_payload_3.json;
https://services.nvd.nist.gov/rest/json/cpes/2.0?resultsPerPage=50&startIndex=0
If you want to follow along, you can grab this script (and the ones to follow) from our tutorial content repository on Github as follows;
git clone https://github.com/signalscorps/tutorials
cd openai-cve2stix
python3 -m venv tutorial_env
source tutorial_env/bin/activate
pip3 install -r requirements.txt
cd examples
Now running the script;
python3 convert_cpes_to_stix_0.py test_payload_3.json
Conversion to STIX completed successfully! Bundle saved to bundle--877792c7-eb26-48b3-8a88-c1d267555ab5.json
It works!
However, no one wants to be grabbing the JSON files as inputs to the script manually. Lets try automating requests to the API.
Input:
The following NVD API endpoint can be used to retrieve CPEs;
GET https://services.nvd.nist.gov/rest/json/cpes/2.0?
This endpoint can be used to easily retrieve information on a single CPE record or a collection of CPE records from the Official CPE Dictionary.
The documentation for it can be found here.
All requests to this endpoint require an apiKey value passed in the header of the request, obtained here. Here is an example.
curl
--location 'https://services.nvd.nist.gov/rest/json/cves/2.0' \
--header 'apiKey: <API_KEY>'
Where <API_KEY> is the API key entered by user running the script via the command line.
Parameters can be passed in the URL of the request. Here is an example of passing the resultsPerPage parameter with the value equal to 50;
GET https://services.nvd.nist.gov/rest/json/cpes/2.0?resultsPerPage=50
All requests should have the URL resultsPerPage set to 50.
Here is the response schema for reference.
Here is a sample payload response returned by the endpoint:
{
"resultsPerPage": 1,
"startIndex": 0,
"totalResults": 187,
"format": "NVD_CPE",
"version": "2.0",
"timestamp": "2023-04-26T06:34:28.333",
"products": [
{
"cpe": {
"deprecated": false,
"cpeName": "cpe:2.3:a:vm2_project:vm2:3.9.4:*:*:*:*:node.js:*:*",
"cpeNameId": "6081D3BE-1BA6-4EBC-AAA3-2114610D1FD7",
"lastModified": "2021-10-20T18:11:01.593",
"created": "2021-10-19T15:09:32.347",
"titles": [
{
"title": "vm2 Project vm2 3.9.4 for Node.js",
"lang": "en"
}
],
"refs": [
{
"ref": "https://www.npmjs.com/package/vm2",
"type": "Product"
},
{
"ref": "https://snyk.io/vuln/SNYK-JS-VM2-1585918",
"type": "Advisory"
},
{
"ref": "https://github.com/patriksimek/vm2/releases",
"type": "Change Log"
}
]
}
}
]
}
Please write a Python 3 script that;
- when executing the script lets the user to specify their API key via the command line
- the script should then print the request made to the NVD API to the command line
- the script should then read the first page of responses and convert the CPE entries to STIX 2.1 Software object using the template shown below;
{
"type": "software",
"spec_version": "2.1",
"id": "software--<A>",
"name": "<B>",
"cpe": "<C>",
"version": "<D>",
"vendor": "<E>",
"object_marking_refs": [
"marking-definition--613f2e26-407d-48c7-9eca-b8e91df99dc9"
],
"extensions": {
"extension-definition--6c453e0f-9895-498f-a273-2e2dda473377": {
"extension_type": "property-extension",
"<F>"
}
}
}
Where:
<A>: is a UUIDv5 generated using thecpevalue using the STIX2 Python library (https://pypi.org/project/stix2/)<B>: is theproducts.cpe.titles.titlevalue in the NVD API response. If more than one value exists, use whereproducts.cpe.titles.langisen.<C>: is theproducts.cpe.cpeNamevalue in the response<D>: is found in theproducts.cpe.cpeNamebetween the fifth and sixth:characters. For example, in thisproducts.cpe.cpeNameiscpe:2.3:a:apple:boot_camp:6.1.14:*:*:*:*:*:*:*,<D>is6.1.14<E>: is found in theproducts.cpe.cpeNamebetween the third and fourth:characters. For example, in thisproducts.cpe.cpeNameiscpe:2.3:a:apple:boot_camp:6.1.14:*:*:*:*:*:*:*,<E>isapple<F>: is the entire value forproducts.cpein the NVD API payload
- When the final CPE has been converted to a STIX software Object, a STIX 2.1 bundle containing all converted CPEs as STIX 2.1 Software Objects should be created and saved in the working directory.
Please also:
- add logic in the script to print any error messages to the command line if the response status code is not 200 (OK) to help debug any issues.
Response:
Here’s a Python 3 script that satisfies the requirements:
Explanation:
- The script prompts the user to enter their API key for the NVD API.
- The API endpoint and parameters are set.
- The headers for the API request are set with the API key.
- The request is made to the API endpoint and the response is checked for success.
- The response is converted to JSON.
- A STIX bundle is created to hold the STIX software objects.
- The CPE records in the response are iterated through and the necessary fields are extracted to create the STIX software objects.
- The STIX software objects are added to the bundle.
- The bundle is serialized to JSON and written to a file in the working directory.
- A success message is printed to the console.
Note that this script requires the requests and stix2 Python packages to be installed. These can be installed via pip install requests stix2.
Review:
Lets try running it.
python3 convert_cpes_to_stix_1.py
Conversion to STIX completed successfully!
It works!
Lets look at the bundle generated;
Here we only see one result, there should be 50. Running the same request with Postman I can see over one million results in total, and thus 50 on the first page.
{
"resultsPerPage": 50,
"startIndex": 0,
"totalResults": 1063290,
"format": "NVD_CPE",
"version": "2.0",
"timestamp": "2023-04-26T07:16:53.503",
"products":
Lets fix that…
Input:
Currently, the script only converts a single CPE records found in the response to a STIX 2.1 Software Objects. It should convert all CPE records in the response to STIX 2.1 Software Objects and add them all to the resulting STIX bundle.
Also please update the script to name the Bundle filename using the bundle ID generated.
Output:
Sure, here is the updated script that will convert all CPE records to STIX 2.1 Software Objects and add them to the resulting STIX bundle, and will name the Bundle filename using the bundle ID generated:
In the updated script, a list bundle_objects is created to store all the software objects created. Then, in the loop that creates the software objects, each object is added to this list using the append() method.
Finally, the Bundle is created using bundle_objects, and the serialized bundle is saved to a file with the name _bundle_{bundle.id}.json, where bundle.id is the ID of the STIX bundle generated.
Review:
python3 convert_cpes_to_stix_2.py
Conversion to STIX completed successfully!
Perfect!
The CPE API offers a range of parameters to filter the response. Lets get GPT to add some to the script.
Input:
That’s perfect.
The NVD CPE API also accepts the following URL parameters;
lastModStartDate: defines earliest modified data of a CPE. Datetime value passed must be in the formatYYYY-MM-DDTHH:MM:SS%2BHH:MM. Here is an example value for reference2021-10-22T13:36:00%2B00:00. If this parameter is used,lastModEndDateparameter must also be passed.lastModEndDate: URL parameters that can be used to identify new or updated CPEs. Datetime format the same aslastModStartDate. If this parameter is used,lastModStartDateparameter must also be passed.
Here is an example of the URL parameters;
GET https://services.nvd.nist.gov/rest/json/cpes/2.0?resultsPerPage=50&lastModStartDate=2021-10-20T18:00:00%2B00:00&lastModEndDate=2021-10-21T00:00:00%2B00:00
Please update the script to allow the user to specify the lastModStartDate and lastModEndDate via the command line when running the script.
Output:
Sure, here’s an updated version of the script that allows the user to specify lastModStartDate and lastModEndDate via the command line arguments:
In this version of the script, we use the argparse module to parse
Review:
python3 convert_cpes_to_stix_3.py --lastModStartDate "2021-10-20T18:00:00%2B00:00" --lastModEndDate "2021-10-21T00:00:00%2B00:00" API_KEY_REDACTED
Request URL: https://services.nvd.nist.gov/rest/json/cpes/2.0?resultsPerPage=50&startIndex=0&lastModStartDate=2021-10-20T18:00:00%2B00:00&lastModEndDate=2021-10-21T00:00:00%2B00:00
Request headers: {'apiKey': 'API_KEY_REDACTED'}
Conversion to STIX completed successfully!
Perfect.
So now all that’s needed is to introduce pagination, because looking at that request there are four pages of CPEs returned (187/50);
{
"resultsPerPage": 50,
"startIndex": 0,
"totalResults": 187,
"format": "NVD_CPE",
"version": "2.0",
"timestamp": "2023-04-25T07:30:43.900",
ChatGPT…
Input:
That’s great.
However, the script only considers the first page of responses (50 CPEs).
You can calculate pages using the following data in header response;
{
"resultsPerPage": 50,
"startIndex": 0,
"totalResults": 187,
"format": "NVD_CPE",
"version": "2.0",
"timestamp": "2023-04-25T07:30:43.900",
If totalResults is greater than resultsPerPage, there are more pages.
You can calculate pages by dividing totalResults/resultsPerPage.
You can see the current page reported in the value of startIndex. Pages are 0 rated (the first page is 0) and iterate by one each time (e.g. 0, 1, 2…).
For example, in the example above, there are four pages (187/50=3.74). The four pages have startIndex values of 0, 1, 2, and 3 respectively.
Requests to the CPE endpoint can also pass the URL parameter startIndex. This defines the page of results to be returned.
Please update the script to paginate through all results returned by the API so that all matching CPE records are captured in the resulting STIX 2.1 Bundle.
Output:
Sure, here’s an updated version of the script that will paginate through all the results and convert them to STIX 2.1 Software objects:
Review:
python3 convert_cpes_to_stix_4.py --lastModStartDate "2021-10-20T18:00:00%2B00:00" --lastModEndDate "2021-10-21T00:00:00%2B00:00" API_KEY_REDACTED
Request URL: https://services.nvd.nist.gov/rest/json/cpes/2.0?resultsPerPage=50&startIndex=0&lastModStartDate=2021-10-20T18:00:00%2B00:00&lastModEndDate=2021-10-21T00:00:00%2B00:00
Request headers: {'apiKey': 'API_KEY_REDACTED'}
Conversion to STIX completed successfully!
Which now returns almost 200 CPEs as expected.
After going through these prompts manually, someone showed me Auto-GPT, which would have made this task MUCH simpler…
Using agents/autonomous AIs
Agent AIs take a user input, break it down into many small individual tasks with help of LLMs and work through them.
They store the individual results, check them if necessary, and then use them as input for subsequent steps. This allows them to handle more complex tasks and access different foundation models (language, code, video, voice, …) and resources (search engines, calculation tools, etc.).
Auto-GPT is just one such autonomous AI, and arguably the most widely used at the time of writing.
I’ve seen people trying to build entire software products using Auto-GPT, so I wanted to see if I could recreate my, by comparison, simplistic requirements for paging through the CPE API.
Setup Auto-GPT
Installing Auto-GPT is easy;
git clone https://github.com/Significant-Gravitas/Auto-GPT.git
cd Auto-GPT
python3 -m venv tutorial_env
source tutorial_env/bin/activate
pip3 install -r requirements.txt
cp .env.template .env
Now find the variable OPENAI_API_KEY and add your OpenAI API key.
You should also uncomment and change the value for # EXECUTE_LOCAL_COMMANDS=True to EXECUTE_LOCAL_COMMANDS=True (allows Auto-GPT to execute commands in the command prompt (cmd, shell). )
Also, before you begin, be sure set a spending limit on your OpenAI account.
Running Auto-GPT
To start Auto-GPT…
python3 -m autogpt
Welcome to Auto-GPT! run with '--help' for more information.
Create an AI-Assistant: input '--manual' to enter manual mode.
Asking user via keyboard...
I want Auto-GPT to:
p.s. you can also run python3 -m autogpt --continuous which requires no human intervention between commands (you can watch the logic of each command in real-time to ensure it doesn’t go off track).
Setting goals for Auto-GPT
You can now set the goal for Auto-GPT. Goals should be specific, but you can also add prompts when Auto-GPT is running to steer its progress towards your goals.
This time I decided to try and build the same script using Auto-GPT, with similar core functionality to cve2stix. Here is the initial brief I set;
Build a Python script to download NVD (National Vulnerability Database) CPE (Common Platform Enumeration) objects, convert each CPE object to a STIX 2.1 Software object representation. For this task you must use the NVD APIs described here to download CPEs: https://nvd.nist.gov/developers/products, and the STIX2 Python library to perform the conversion: https://pypi.org/project/stix2/. The conversion from NVD CPE representation to STIX 2.1 representation should follow the data mapping describe here: https://www.signalscorps.com/blog/2023/building-cve2stix-3-nvd-to-stix-2_1/. The script should also periodically check the NVD CPE API for new CPE additions, CPE updates, or CPE removals and add/update the associated STIX object accordingly. You should include full automated test coverage for the script. When testing the script, be sure to create a local virtual environment to run it in. Once the script has been tested successfully, include a detailed README.md that explains how to use the script, how tests can be run, and any other information that might be useful for developers to further enhance the script. When you have completed the task to achieve goals 1 - 4, save the code to the local workspace in a directory call cpe2stix and terminate.
Entering the brief sets the AI agent to work…
THOUGHTS: I need to start by researching the NVD API and the STIX2 Python library to understand how to use them to download and convert CPE objects to STIX 2.1 Software objects. I should also consider how to periodically check for updates to the NVD CPE API and update the associated STIX objects accordingly. I will start by searching for documentation on these topics.
REASONING: Researching the necessary tools and APIs is the first step in building a Python script to download and convert CPE objects to STIX 2.1 Software objects. This will help me understand the requirements and limitations of the project and allow me to plan accordingly.
PLAN:
- Research the NVD API and STIX2 Python library
- Determine how to use them to download and convert CPE objects to STIX 2.1 Software objects
- Consider how to periodically check for updates to the NVD CPE API and update the associated STIX objects accordingly
CRITICISM: I need to ensure that I am thorough in my research and take the time to fully understand the tools and APIs I will be using. Rushing through this step could lead to errors and inefficiencies in the final product.
NEXT ACTION: COMMAND = google ARGUMENTS = {'input': 'NVD API documentation'}
Enter 'y' to authorise command, 'y -N' to run N continuous commands, 'n' to exit program, or enter feedback for ...
As it continues to research, you will be able to follow Auto-GPT’s logic at each step;
THOUGHTS: Now that I have found the NVD API documentation, I need to research the STIX2 Python library to understand how to use it to convert CPE objects to STIX 2.1 Software objects. I will start by searching for documentation on the library.
REASONING: Understanding how to use the STIX2 Python library is crucial to the success of this project, as it will allow me to convert the downloaded CPE objects to STIX 2.1 Software objects. This will help me plan the implementation of the script and ensure that I am using the library correctly.
PLAN:
- Research the STIX2 Python library documentation
- Determine how to use the library to convert CPE objects to STIX 2.1 Software objects
- Plan the implementation of the script
CRITICISM: I need to ensure that I am thorough in my research and take the time to fully understand the STIX2 Python library. Rushing through this step could lead to errors and inefficiencies in the final product.
NEXT ACTION: COMMAND = google ARGUMENTS = {'input': 'STIX2 Python library documentation'}
Enter 'y' to authorise command, 'y -N' to run N continuous commands, 'n' to exit program, or enter feedback for ...
Instead of just authorising a command (y) you can still provide text feedback to the agent between commands if you don’t agree with its approach.
For example, I saw it trying to clone a repository for CPE information, instead of using the NVD API as instructed. As such, instead of allowing it to continue, I intervened;
Please only use the NVD API described here https://nvd.nist.gov/developers/products to download CPE data
Auto-GPT will then adjust based on your feedback. In my case, Auto-GPT proceeded by correcting itself, starting to learn how to use the NVD API.
More on how I get on with Auto-GPT soon!
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