CVE-2026-26006
Agpt Autogpt Platform 0.4.0 – 0.6.32
Raw vector
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:HSummary
CVE-2026-26006 is a medium-severity Inefficient Regular Expression Complexity (CWE-1333) vulnerability in Agpt Autogpt Platform. Its CVSS base score is 6.5 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique Endpoint Denial of Service (T1499); ranked at the 39th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
This vulnerability is AI-related — categorised as AI Agent Protocols and Integrations; in the Supply Chain and Deployment risk domain.
The strongest mitigations our analysis identified map to SA-11 (Developer Testing and Evaluation) and SA-15 (Development Process, Standards, and Tools) — see the control section below for these in your framework.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-6239
Vulnerability Data
AutoGPT is a platform that allows users to create, deploy, and manage continuous artificial intelligence agents that automate complex workflows. The autogpt before 0.6.32 is vulnerable to Regular Expression Denial of Service due to the use of regex at Code…
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Extraction Block. The two Regex are used containing the corresponding dangerous patterns \s+[\s\S]*? and \s+(.*?). They share a common characteristic — the combination of two adjacent quantifiers that can match the same space character (\s). As a result, an attacker can supply a long sequence of space characters to trigger excessive regex backtracking, potentially leading to a Denial of Service (DoS). This vulnerability is fixed in 0.6.32.
- CWE(s)
AI Security AnalysisAI
- AI Category
- AI Agent Protocols and Integrations
- Risk Domain
- Supply Chain and Deployment
- OWASP Top 10 for LLMs 2025
- None mapped
- Classification Reason
- Matched keywords: artificial intelligence, autogpt
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Mitigating Controls (NIST 800-53 r5) AI
Developer testing and evaluation can discover inefficient regex patterns via performance or static analysis.
Development standards and tools can require safe regex construction and forbid known exponential patterns.
Denial-of-service protections limit resource exhaustion caused by expensive regex evaluation.
Input validation can constrain data that would otherwise trigger worst-case regex complexity.
Mitigating Controls (NIST CSF 2.0) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→CSF cross-walk (authority under review) — links open the control.
Mitigating Controls (ISO/IEC 27001:2022 Annex A) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→ISO cross-walk (authority under review) — links open the control.
Security testing can detect and reject regex patterns with exponential worst-case complexity.
Secure development lifecycle mandates review of algorithmic efficiency, directly addressing ReDoS-prone regex.
Application security requirements can specify input-validation rules that limit regex complexity.
Secure architecture principles encourage avoidance of computationally expensive constructs such as catastrophic backtracking.
Secure coding standards explicitly prohibit or limit the use of inefficient regular expressions.