CVE-2025-34072: Data exfiltration vulnerability in Anthropic Slack MCP Server
Attack on AI2 Disclosed vulnerabilityInfrastructure vulnerabilityAgent hijack
A data exfiltration vulnerability affects Anthropic's deprecated Slack Model Context Protocol Server through automatic link unfurling. Manipulated AI agent messages can cause zero-click data exfiltration via external preview requests.
disclosed CVENo confirmed exploitation, so this record is tracked as a disclosed vulnerability and not counted as an incident. It moves into the counts if CISA or the vendor confirms exploitation. Why
Details
- type
- Attack on AIAn AI model, agent or AI-powered product was the thing exploited, abused or leaked.
- categories
- Infrastructure vulnerabilityprimaryCVEs and advisories in AI frameworks, inference servers, MCP servers, AI developer tools and hosting stacks.
- Agent hijackAn AI agent is tricked into unauthorized actions: tool misuse, data exfiltration through the agent, or acting against its principal.
- Infrastructure vulnerabilityprimary
- owasp llm top 10
- mitre atlas
- Both rows are derived from the type and categories (OWASP 2025 edition, ATLAS release 2026.09), not classified per record. How
- severity
- 2 · Disclosed vulnerabilityCVE or vendor advisory, patched or patchable, no confirmed exploitation.
- targets
- Anthropic, Framework / tooling
- products
- Slack Model Context Protocol Server
- incident date
- 2 Jul 2025
- first reported
- 2 Jul 2025
- origin
- NVDVulnerability record from NVD / the GitHub Advisory Database. This product uses the NVD API but is not endorsed or certified by the NVD.
- classifier confidence
- 0.95 · published at or above 0.80; see the methodology
- tags
- CVE-2025-34072 · data-exfiltration · mcp
- record
- created 2026-10-18 10:04Z · updated 2026-10-18 10:04Z · json
Sources · 1
- 2025-07-02CVE-2025-34072: A data exfiltration vulnerability exists in Anthropic’s deprecated Slack Model Context Protocol (MCP) Server via automatic link…NVD · nvd.nist.gov/vuln/detail/CVE-2025-34072
Titles and links belong to their publishers. The summary above is written by GCD AI RADAR in its own words; data is CC BY-SA 4.0.
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