Skip to content

[uk-ai-resilience] [security] Escalate: XPIA cache-memory poisoning unresolved >6 months — implement sanitization layer (Tier C [Content truncated due to length] #47114

Description

@github-actions

Escalation Notice

This is an escalation of #45777 which has been open since July 2025 (>6 months). The XPIA cache-memory poisoning surface remains unmitigated and is the highest composite risk (8.5/10) finding in this week's UK AI governance assessment.

Tier & Risk Scoring

Dimension Score
Tier C — Restricted Pending Review
Composite Risk 8.5 / 10
Remediation Priority Critical
SLA 14 days (by 2026-08-04)
Exposure amplification 5/5 — cross-run agentic poisoning with AI autonomy multiplier
Patchability 2/5 — requires architectural sanitization layer
Detectability 2/5 — poisoned cache content is silent until triggered

Description

The migrate-legacy-files path and cache-memory ingestion layer in pkg/workflow/cache.go reads content from prior agentic runs without validation. An adversarial workflow run could write crafted content to cache memory that, on subsequent runs, is injected into LLM prompts without sanitization — a classic cross-run XPIA (Cross-Prompt Injection Attack).

Related issues: #28830 (cache-memory cross-run poisoning), #28775 (sanitize repo-memory and cache-memory content).

Why This Is an Escalation

  • Age: Open since ~July 2025 — MTTR proxy is >6 months, well beyond the 30-day Tier C target.
  • AI amplification: gh-aw runs agentic pipelines with actions: write, issues: write, and pull-requests: write permissions. Poisoned cache feeding into LLM prompts could cause the agent to take unauthorized destructive actions.
  • No mitigation in place: No sanitization, no allowlist, no content-integrity check exists on cache reads.

Required Remediation Actions

  1. Short-term (7 days): Add content length and format validation on cache memory reads; reject entries exceeding reasonable bounds or containing obvious injection patterns.
  2. Medium-term (14 days): Implement a sanitization layer that strips or escapes prompt-injection patterns before cache content is appended to LLM context.
  3. Long-term: Introduce content-integrity signatures for cache entries so runs can verify they're reading their own prior output, not adversarially injected content.
  4. Document threat model and mitigations in an ADR.

Exception Governance

  • Threat hypothesis: Adversarial workflow run writes crafted cache content; subsequent run injects it into AI model context without sanitization.
  • Exploit acceleration: High — agentic pipelines with write permissions are prime targets for prompt injection.
  • Operational weakness: No sanitization layer on cache reads.
  • Exception expiry: 2026-08-07 (must have at minimum short-term mitigation by this date).
  • Mitigation plan: See remediation actions above.

References:

Generated by UK AI Operational Resilience · sonnet46 88.1 AIC · ⌖ 6.03 AIC · ⊞ 5.2K ·

Metadata

Metadata

Assignees

No one assigned

    Type

    No type

    Projects

    No projects

    Milestone

    No milestone

    Relationships

    None yet

    Development

    No branches or pull requests

    Issue actions