Memory / context poisoning
Malicious instructions persisted in assistant memory across sessions
categoryAI/ML and emerging attacksseverityHighlabnot yet measured
Example: SpAIware
Classification
16 values: 5 imported, 1 derived, 10 machine-classified. What do these mean?
Exploitability
| Attack vector | AI model manipulation |
|---|---|
| Reach (CVSS) | Network |
| Attack complexity | Low |
| Privileges required | None |
| User interaction | Passive |
| Attacker skill required | Medium |
| Resources required | Low |
| Likelihood / prevalence | Medium |
| Maturity | Emerging |
Impact & scope
| Severity | High |
|---|---|
| Impact | ConfidentialityIntegrity |
| Platform | AI System |
| Environment | AI system |
| Target asset class | ML model / agent |
| Kill-chain phase (tactic) | Persistence |
Detection & response
Mitigated by 2
Framework references
- Primary source: https://embracethered.com/blog/posts/2024/chatgpt-macos-app-persistent-data-exfiltration/
- owasp-asi: ASI06 (primary)
- atlas: AML.T0080.000
Evidence & sources
- ev-0001 (Cyber Attack Taxonomy) — Name, definition and Example/ID taken verbatim from the 'AI/ML and emerging attacks' table, line 635 of Cyber-Attack-Taxonomy.md
- ev-0002 (Seeded-record enrichment run 2026-09-30 (crosswalk + facet classification)) — Crosswalk to atlas:AML.T0080.000 as the nearest framework entries; ids verified to exist in the cached catalogues.