ASR AI Security Radar
Methodology Recent Incidents Get Notified

Back to incidents

AI security incident: CVE-2025-32393 (NVD)

Incident date: February 5, 2026 | Published: February 14, 2026 | Source: NVD | Classification confidence: 75%

This incident is part of the public archive and includes explicit AI-related signals from the cited source material. Review methodology.

AutoGPT is a platform that allows users to create, deploy, and manage continuous artificial intelligence agents that automate complex workflows. Prior to autogpt-platform-beta-v0.6.32, there is a DoS vulnerability in ReadRSSFeedBlock. In RSSBlock, feedparser.parser is called to obtain the XML file according to the URL input by the user, parse the XML, and finally obtain the parsed result. However, during the parsing process, there is no limit on the parsing time and the resources that can be allocated for parsing. When a malicious user lets RSSBlock parse a carefully constructed, deep XML, it will cause memory resources to be exhausted, eventually causing DoS. This issue has been patched in autogpt-platform-beta-v0.6.32.

Why This Is AI-Related

This page is treated as AI-specific because the source material references artificial intelligence, which places the issue inside an AI workflow, model, assistant, or supporting dependency rather than a generic software bulletin.

  • artificial intelligence

Affected Workflow

Check inference endpoints, parsing layers, queues, and file processing jobs that support AI features.

Likely Attack Path

An attacker can drive resource exhaustion or crash conditions in the vulnerable component through crafted traffic or content.

Impact

The advisory describes an availability or resource-exhaustion path that can disrupt AI-serving components and supporting automation. Severity HIGH. Classification confidence 75%. Source channel NVD.

Detection And Triage Signals

  • Latency spikes or worker restarts on AI-serving endpoints
  • Memory or CPU saturation after malformed requests or artifacts
  • Queue backlogs, timeouts, or repeated crash loops in model services

Recommended Response

  • Identify inference endpoints, parsing jobs, or queues that rely on the affected component.
  • Apply vendor mitigations and add rate, size, or input controls to reduce exhaustion risk during triage.
  • Monitor latency, restart frequency, queue backlog, and saturation indicators for active disruption.

Compliance And Business Impact

Availability failures can interrupt customer-facing AI features and force emergency rollback or capacity isolation.

Sources

Want alerts like this in real time?

Get notified with incident context, likely impact, and response guidance.

Get Notified

More incidents