AutoGPT is a platform that allows users to create, deploy, and manage continuous artificial intelligence agents that automate complex workflows. Prior to 0.6.1, AutoGPT allows of leakage of cross-domain cookies and protected headers in requests redirect. AutoGPT uses a wrapper around the requests python library, located in autogpt_platform/backend/backend/util/request.py. In this wrapper, redirects are specifically NOT followed for the first request. If the wrapper is used with allow_redirects set to True (which is the default), any redirect is not followed by the initial request, but rather re-requested by the wrapper using the new location. However, there is a fundamental flaw in manually re-requesting the new location: it does not account for security-sensitive headers which should not be sent cross-origin, such as the Authorization and Proxy-Authorization header, and cookies. For example in autogpt_platform/backend/backend/blocks/github/_api.py, an Authorization header is set when retrieving data from the GitHub API. However, if GitHub suffers from an open redirect vulnerability (such as the made-up example of https://api.github.com/repos/{owner}/{repo}/issues/comments/{comment_id}/../../../../../redirect/?url=https://joshua.hu/), and the script can be coerced into visiting it with the Authorization header, the GitHub credentials in the Authorization header will be leaked. This allows leaking auth headers and private cookies. This vulnerability is fixed in 0.6.1.
CVE-2025-31491
This high-severity CVE scores 8.6 under NVD CVSS v3. EPSS exploit probability: 0.5%, top 63% of all CVEs by exploit prediction. GitHub Security Advisory data not yet ingested — confidence will rise once GHSA publishes (typical lag: hours to days for open-source ecosystem CVEs; never for infrastructure-only CVEs).
- High severity, but no confirmed exploitation yet
No vendor fix yet — apply a workaround or compensating control (WAF / firewall / segmentation) and watch for a patch.
- CVSS v3
- 8.6
- EG Score
- 8.6(medium)
- EG Risk
- 70(Attend)EG Risk 70/100SSVC: Attend
EG Risk is EchelonGraph's 0–100 priority score: it fuses intrinsic severity with real-world exploitation and automatability so you can rank equal-severity CVEs and fix the most dangerous first. Higher = act sooner. Distinct from the 0–10 EG Score (severity).
How it’s computedSeverity86% × 45%Exploitation40% × 40%Automatability100% × 15%Action: Remediate soon — notable exploitation risk. - EPSS
- 37.0%
- KEV
- Not listed
Published
April 15, 2025
Last Modified
August 5, 2025
References (1)
- security-advisories@githubhttps://github.com/Significant-Gravitas/AutoGPT/security/advisories/GHSA-ggcm-93qg-gfhp
Weakness Classification(2)
MITRE Common Weakness Enumeration — the root-cause categories this CVE belongs to.
Data Freshness Timeline
(refreshed 12× in last 7d / 47× in last 30d)
Each row is a source pipeline that fetched or updated this CVE on that date, with what changed. For example, "NVD update" means NVD published or revised its analysis for this CVE; "MITRE cvelistV5" means we ingested or refreshed it from the CNA feed. Most recent first.
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Related CVEs(same CWE)
Same CWE
10 shownCWE-200 · CWE-601
Frequently asked(5)
What is CVE-2025-31491?
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Dependency Blast Radius
Explore the affected products and dependency analysis for CVE-2025-31491
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