CVE-2026-26006 is a vulnerability classified under CWE-1333, involving inefficient regular expression complexity in the Significant-Gravitas AutoGPT platform, specifically versions from 0.4.0 up to 0.6.32. AutoGPT enables users to deploy continuous AI agents to automate complex workflows. The vulnerability stems from two regex patterns used in the Code Extraction Block: "\s+[\s\S]*?" and "\s+(.*?)". Both patterns contain adjacent quantifiers that can match the same whitespace character (\s), leading to catastrophic backtracking when processing long sequences of spaces. An attacker can exploit this by sending specially crafted input containing long whitespace sequences, causing the regex engine to consume excessive CPU resources, resulting in a Denial of Service (DoS). The attack vector is network-based, requiring low privileges and no user interaction, making it relatively easy to exploit remotely. The vulnerability affects availability but does not compromise confidentiality or integrity. The issue was addressed in AutoGPT version 0.6.32, where the regex patterns were presumably optimized or replaced to prevent excessive backtracking. No public exploits are currently known, but the medium CVSS score (6.5) reflects the moderate impact and ease of exploitation. Organizations relying on AutoGPT for AI-driven automation should prioritize patching to avoid service disruptions.

For European organizations, the primary impact of CVE-2026-26006 is the potential for Denial of Service attacks against AI automation workflows powered by vulnerable AutoGPT versions. Disruptions could affect business-critical processes automated by AI agents, leading to operational downtime and productivity loss. Since the vulnerability does not affect data confidentiality or integrity, the risk of data breaches is low. However, availability issues could cascade into delays in decision-making, customer service interruptions, or failure in automated monitoring systems. Organizations with extensive AI deployments or those integrating AutoGPT into their infrastructure are at higher risk. The ease of exploitation (network accessible, low privileges, no user interaction) increases the likelihood of opportunistic attacks, especially in environments exposed to untrusted inputs. Given the growing adoption of AI automation in sectors like finance, manufacturing, and public services across Europe, the impact could be significant if unpatched.

The most effective mitigation is to upgrade AutoGPT to version 0.6.32 or later, where the regex inefficiencies have been resolved. Until upgrading is possible, organizations should implement input validation and sanitization to limit or reject unusually long sequences of whitespace characters in inputs processed by AutoGPT. Network-level protections such as rate limiting, Web Application Firewalls (WAFs), or Intrusion Prevention Systems (IPS) can help detect and block suspicious traffic patterns indicative of ReDoS attempts. Monitoring CPU and memory usage of AutoGPT instances can provide early warning signs of exploitation attempts. Additionally, isolating AutoGPT services in segmented network zones reduces the blast radius of potential DoS attacks. Security teams should review logs for anomalies related to regex processing delays and prepare incident response plans for availability disruptions. Finally, educating developers and operators about safe regex usage and the risks of ReDoS can prevent similar issues in future AI automation projects.