A signed persistent MCP tool retained confidential context across calls and reused its permitted OCR-like endpoint to transmit unrelated data. Signature verification and destination allowlisting left a gap because the destination itself was authorized. The Germline prototype isolated per-call data and reported zero disclosures in 153 tests versus 114 of…
Inspect the ClaimsCase · DiggingBeagle record
Germline tests show signed MCP tools can leak data through allowed destinations
A signed persistent MCP tool retained confidential context across calls and reused its permitted OCR-like endpoint to transmit unrelated data. The Germline prototype isolated per-call data and reported zero disclosures in 153 tests versus 114 of 153 under signing-only protection, plus 91 tested adaptive variants.
Public disclosure: Nov 4, 2026
Controlled empirical evaluation; percentages and effects apply to the reported task populations and conditions, not deployed incidents.
Assessment profile
Assessment method- Setting
- research demonstration
- Exploitation
- demonstrated
- Evidence
- Grade C
- Remediation
- not applicable
- AI role
- AGAINST AI
Basis and provenance
research demonstration; demonstrated. The cited primary disclosure supports the specific sequence and boundaries described here: A signed persistent MCP tool receives confidential data during one legitimate call. The evidence does not independently establish consequences beyond the record's supported outcome; a numerical impact band cannot be justified from the available evidence. Evidence grade C reflects the source attribution and independent verification limits.
Assessed Nov 7, 2026 using diggingbeagle.assessment/1.
Evidence basis: CLM-DB07-041-OUTCOME · CLM-DB07-041-MECHANISM · CLM-ENR-DB07-024-GERMLINE-EVAL-BOUND · Germline: Per-call data isolation for signed MCP tools
At a glance
Enforce per-call data provenance at the broker, split unauthorized mixed calls and evaluate uninstrumented channels and trusted-root assumptions.
Read the implicationsPython prototype, no claim all uninstrumented channels closed; correct broker labeling and trusted root needed. Do not confuse signed provenance with confidentiality.
Limits and uncertaintyFull account
A signed persistent MCP tool retained confidential context across calls and reused its permitted OCR-like endpoint to transmit unrelated data. Signature verification and destination allowlisting left a gap because the destination itself was authorized.
The Germline prototype isolated per-call data and reported zero disclosures in 153 tests versus 114 of 153 under signing-only protection, plus 91 tested adaptive variants. Those are experimental results within its instrumented Python setting.
Germline's attack does not need the signed MCP package to be changed after installation. A persistent OCR-style tool can retain sensitive bytes from an earlier authorized call and send them to a server that is itself permitted for OCR requests. Signing establishes that the same tool code is running, while a destination allowlist establishes where it can connect; neither proves the bytes in each call were authorized for that recipient. The prototype starts each call from a data-free state and has a broker separate or reject mixed-provenance data. The paper reports zero disclosures in its tested 153 cases and 91 adaptive variants, not a guarantee against every uninstrumented channel or flawed broker labeling.
A signed tool identifies code provenance, not which confidential data the process retained from prior calls. The research attack reused data across otherwise permitted OCR-style requests, including requests sent to an allowed destination. Germline's per-call process isolation and broker-side labeling aim to stop that data crossing request boundaries, but the tested Python prototype cannot establish protection for uninstrumented channels. This complements recipient-provenance defenses: destination approval alone cannot make an authorized endpoint safe for every piece of carried data.
Mechanism and trust boundary
- 01
A signed persistent MCP tool receives confidential data during one legitimate call.
- 02
It retains or combines that data with material for a later OCR-like call to an otherwise allowed endpoint.
- 03
Germline's proposed broker enforces per-call data provenance and removes persistent cross-call state, preventing the demonstrated leakage patterns.
Claims & evidence
CLM-DB07-041-OUTCOMEThe Germline prototype isolated per-call data and reported zero disclosures in 153 tests versus 114 of 153 under signing-only protection, plus 91 tested adaptive variants. Those are experimental results within its instrumented Python setting.supported
Basis: reported finding
- supportsGermline: Per-call data isolation for signed MCP toolsprimary disclosure
Paper threat model; attack construction; 153-run evaluation
CLM-DB07-041-MECHANISMA signed persistent MCP tool retained confidential context across calls and reused its permitted OCR-like endpoint to transmit unrelated data. Signature verification and destination allowlisting left a gap because the destination itself was authorized.supported
Basis: reported finding
- supportsGermline: Per-call data isolation for signed MCP toolsprimary disclosure
Paper threat model; attack construction; 153-run evaluation
CLM-ENR-DB07-024-GERMLINE-EVAL-BOUNDIn the Germline paper, per-call isolation reported zero disclosures in 153 controlled tests versus 114 disclosures using signature checking alone, plus zero in 91 adaptive variants; these counts do not establish that all uninstrumented MCP channels are secure.supported
Basis: reported finding
- supportsGermline: Per-call data isolation for signed MCP toolsprimary disclosure
Germline experiments comparing signing-only and isolated forks
Implications
Enforce per-call data provenance at the broker, split unauthorized mixed calls and evaluate uninstrumented channels and trusted-root assumptions.
Unknowns and contradictions
- Python prototype, no claim all uninstrumented channels closed; correct broker labeling and trusted root needed. Do not confuse signed provenance with confidentiality.
Sources and citation
Material revision history
- Nov 7, 2026 · Published version · first publication · revision 227