total-agent-memory
PyPI
v12.4.0
Published by vbcherepanov — no publish provenance, so origin is unverified, but the source is public: the repository link below is self-declared yet readable, so you can inspect the code before adopting it.
The grade answers one question — how safe is this server for you to adopt — so it is computed in two auditable stages. Nothing below is an opinion or an LLM's guess; every line is a real term the deterministic engine applied, and the same input always yields the same number.
1. Threat score — 100 − 0 = 100. What the published surface and source actually contain:
The deterministic scan raised no scored threat in the surface it inspected — the threat score stayed at 100. Capability observations and advisory notes are recorded but never lower it.
2. Client adoption risk — 100 − 11 = 89. Three small, subtract-only factors that reflect your risk in adopting it — a clean scan proves less on a powerful, unverified or barely-inspectable package, so the grade says so plainly:
| Points | Adoption-risk factor |
|---|---|
| −10 | capability blast radius (critical) — client exposure if the model is manipulated |
| −1 | publisher verification (public source) — no provenance, but the source is public and inspectable |
Capability observations and info notes are shown under Findings but never scored.
Open any row's finding below for the file, line and evidence behind a deduction.
This server (without client built-ins) exposes a complete data-exfiltration chain: memory_get → memory_perf_report → memory_eval_contradictions. Untrusted input is ingested, private data is read, and it can be sent to an external sink via the agent composing the tools (→). Static analysis proves the primitive exists, not that a specific run will occur.
Fix: Remove one leg of the trifecta: isolate untrusted-input tools from secret-reading tools and from egress tools, or require human approval between them.
Location: flow memory_get → memory_perf_report → memory_eval_contradictions
Tool "memory_eval_locomo" appears to run shell commands or evaluate code (keyword "eval" in tool name). Arbitrary execution driven by model input is one of the most dangerous MCP capabilities; combined with any untrusted input it becomes RCE.
Fix: Sandbox execution, allowlist commands/arguments, and never pass model output to a shell unescaped.
Location: tool memory_eval_locomo
Tool "memory_eval_recall" appears to run shell commands or evaluate code (keyword "eval" in tool name). Arbitrary execution driven by model input is one of the most dangerous MCP capabilities; combined with any untrusted input it becomes RCE.
Fix: Sandbox execution, allowlist commands/arguments, and never pass model output to a shell unescaped.
Location: tool memory_eval_recall
Tool "memory_eval_temporal" appears to run shell commands or evaluate code (keyword "eval" in tool name). Arbitrary execution driven by model input is one of the most dangerous MCP capabilities; combined with any untrusted input it becomes RCE.
Fix: Sandbox execution, allowlist commands/arguments, and never pass model output to a shell unescaped.
Location: tool memory_eval_temporal
Tool "memory_eval_entity_consistency" appears to run shell commands or evaluate code (keyword "eval" in tool name). Arbitrary execution driven by model input is one of the most dangerous MCP capabilities; combined with any untrusted input it becomes RCE.
Fix: Sandbox execution, allowlist commands/arguments, and never pass model output to a shell unescaped.
Location: tool memory_eval_entity_consistency
Tool "memory_eval_contradictions" appears to run shell commands or evaluate code (keyword "eval" in tool name). Arbitrary execution driven by model input is one of the most dangerous MCP capabilities; combined with any untrusted input it becomes RCE.
Fix: Sandbox execution, allowlist commands/arguments, and never pass model output to a shell unescaped.
Location: tool memory_eval_contradictions
Tool "memory_eval_long_context" appears to run shell commands or evaluate code (keyword "eval" in tool name). Arbitrary execution driven by model input is one of the most dangerous MCP capabilities; combined with any untrusted input it becomes RCE.
Fix: Sandbox execution, allowlist commands/arguments, and never pass model output to a shell unescaped.
Location: tool memory_eval_long_context
In the server's implementation (`src/dashboard.py:811`): Spawning a shell/process is command-execution capability; with unsanitized tool input it is command injection / RCE. This is read from the code itself — not from the tool description — so a poisoned server cannot hide it behind honest-looking metadata.
Evidence: try: result = subprocess.run( ["launchctl", "list"], capture_output=True, text=True, t
Fix: Review this call path: confirm it never receives unsanitized tool input, constrain it, or remove it. Treat a server whose code reaches these sinks as high-capability regardless of what its tools claim.
Location: server src/dashboard.py
In the server's implementation (`src/reflection/scheduler.py:218`): Spawning a shell/process is command-execution capability; with unsanitized tool input it is command injection / RCE. This is read from the code itself — not from the tool description — so a poisoned server cannot hide it behind honest-looking metadata.
Evidence: = "1" result = subprocess.run( [OLLAMA_BIN, "run", model, prompt], capture_output=True,
Fix: Review this call path: confirm it never receives unsanitized tool input, constrain it, or remove it. Treat a server whose code reaches these sinks as high-capability regardless of what its tools claim.
Location: server src/reflection/scheduler.py
In the server's implementation (`src/server.py:6828`): Spawning a shell/process is command-execution capability; with unsanitized tool input it is command injection / RCE. This is read from the code itself — not from the tool description — so a poisoned server cannot hide it behind honest-looking metadata.
Evidence: try: return subprocess.check_output( ["git", "rev-parse", "--abbrev-ref", "HEAD"], s
Fix: Review this call path: confirm it never receives unsanitized tool input, constrain it, or remove it. Treat a server whose code reaches these sinks as high-capability regardless of what its tools claim.
Location: server src/server.py
In the server's implementation (`src/tools/brain_autonomy.py:57`): Spawning a shell/process is command-execution capability; with unsanitized tool input it is command injection / RCE. This is read from the code itself — not from the tool description — so a poisoned server cannot hide it behind honest-looking metadata.
Evidence: = "1" result = subprocess.run( [OLLAMA_BIN, "run", model, prompt], capture_output=True,
Fix: Review this call path: confirm it never receives unsanitized tool input, constrain it, or remove it. Treat a server whose code reaches these sinks as high-capability regardless of what its tools claim.
Location: server src/tools/brain_autonomy.py
In the server's implementation (`src/tools/brain_health.py:57`): Spawning a shell/process is command-execution capability; with unsanitized tool input it is command injection / RCE. This is read from the code itself — not from the tool description — so a poisoned server cannot hide it behind honest-looking metadata.
Evidence: try: proc = subprocess.run( ["launchctl", "list"], capture_output=True,
Fix: Review this call path: confirm it never receives unsanitized tool input, constrain it, or remove it. Treat a server whose code reaches these sinks as high-capability regardless of what its tools claim.
Location: server src/tools/brain_health.py
In the server's implementation (`src/tools/check_updates.py:63`): Spawning a shell/process is command-execution capability; with unsanitized tool input it is command injection / RCE. This is read from the code itself — not from the tool description — so a poisoned server cannot hide it behind honest-looking metadata.
Evidence: n None try: subprocess.run( ["git", "fetch", "--tags", "--quiet"], cwd=ROOT, check=True, timeout
Fix: Review this call path: confirm it never receives unsanitized tool input, constrain it, or remove it. Treat a server whose code reaches these sinks as high-capability regardless of what its tools claim.
Location: server src/tools/check_updates.py
In the server's implementation (`src/tools/cross_project.py:132`): Spawning a shell/process is command-execution capability; with unsanitized tool input it is command injection / RCE. This is read from the code itself — not from the tool description — so a poisoned server cannot hide it behind honest-looking metadata.
Evidence: = "1" result = subprocess.run( [OLLAMA_BIN, "run", model, prompt], capture_output=True,
Fix: Review this call path: confirm it never receives unsanitized tool input, constrain it, or remove it. Treat a server whose code reaches these sinks as high-capability regardless of what its tools claim.
Location: server src/tools/cross_project.py
In the server's implementation (`src/tools/git_observer.py:136`): Spawning a shell/process is command-execution capability; with unsanitized tool input it is command injection / RCE. This is read from the code itself — not from the tool description — so a poisoned server cannot hide it behind honest-looking metadata.
Evidence: = "1" result = subprocess.run( [OLLAMA_BIN, "run", model, prompt], capture_output=True,
Fix: Review this call path: confirm it never receives unsanitized tool input, constrain it, or remove it. Treat a server whose code reaches these sinks as high-capability regardless of what its tools claim.
Location: server src/tools/git_observer.py
In the server's implementation (`src/tools/idea_engine.py:78`): Spawning a shell/process is command-execution capability; with unsanitized tool input it is command injection / RCE. This is read from the code itself — not from the tool description — so a poisoned server cannot hide it behind honest-looking metadata.
Evidence: = "1" result = subprocess.run( [OLLAMA_BIN, "run", model, prompt], capture_output=True,
Fix: Review this call path: confirm it never receives unsanitized tool input, constrain it, or remove it. Treat a server whose code reaches these sinks as high-capability regardless of what its tools claim.
Location: server src/tools/idea_engine.py
In the server's implementation (`src/tools/improve_search.py:72`): Spawning a shell/process is command-execution capability; with unsanitized tool input it is command injection / RCE. This is read from the code itself — not from the tool description — so a poisoned server cannot hide it behind honest-looking metadata.
Evidence: try: result = subprocess.run( ["/usr/local/bin/ollama", "list"], capture_output=True,
Fix: Review this call path: confirm it never receives unsanitized tool input, constrain it, or remove it. Treat a server whose code reaches these sinks as high-capability regardless of what its tools claim.
Location: server src/tools/improve_search.py
Tool "memory_eval_locomo" can mutate/egress but declares no destructiveHint. Clients that don't default to spec-safe behavior may not prompt before running it.
Fix: Declare accurate annotations, and gate destructive tools on user confirmation regardless.
Location: tool memory_eval_locomo
Tool "memory_eval_recall" can mutate/egress but declares no destructiveHint. Clients that don't default to spec-safe behavior may not prompt before running it.
Fix: Declare accurate annotations, and gate destructive tools on user confirmation regardless.
Location: tool memory_eval_recall
Tool "memory_eval_temporal" can mutate/egress but declares no destructiveHint. Clients that don't default to spec-safe behavior may not prompt before running it.
Fix: Declare accurate annotations, and gate destructive tools on user confirmation regardless.
Location: tool memory_eval_temporal
Tool "memory_eval_entity_consistency" can mutate/egress but declares no destructiveHint. Clients that don't default to spec-safe behavior may not prompt before running it.
Fix: Declare accurate annotations, and gate destructive tools on user confirmation regardless.
Location: tool memory_eval_entity_consistency
Tool "memory_eval_contradictions" can mutate/egress but declares no destructiveHint. Clients that don't default to spec-safe behavior may not prompt before running it.
Fix: Declare accurate annotations, and gate destructive tools on user confirmation regardless.
Location: tool memory_eval_contradictions
Tool "memory_eval_long_context" can mutate/egress but declares no destructiveHint. Clients that don't default to spec-safe behavior may not prompt before running it.
Fix: Declare accurate annotations, and gate destructive tools on user confirmation regardless.
Location: tool memory_eval_long_context
Each tool and what it can reach — statically extracted from the published source.
memory_eval_contradictionsruns code / shellmemory_eval_entity_consistencyruns code / shellmemory_eval_locomoruns code / shellmemory_eval_long_contextruns code / shellmemory_eval_recallruns code / shellmemory_eval_temporalruns code / shellmemory_getingests untrusted inputmemory_perf_reportreads sensitive datamemory_timelineingests untrusted inputanalogizeno sensitive capabilitybenchmarkno sensitive capabilityclassify_taskno sensitive capabilityfile_contextno sensitive capabilityingest_codebaseno sensitive capabilitykg_add_factno sensitive capabilitykg_atno sensitive capabilitykg_invalidate_factno sensitive capabilitykg_timelineno sensitive capabilitylearn_errorno sensitive capabilitylist_intentsno sensitive capabilitymemory_associateno sensitive capabilitymemory_conceptsno sensitive capabilitymemory_consolidateno sensitive capabilitymemory_consolidate_statusno sensitive capabilitymemory_context_buildno sensitive capabilitymemory_deleteno sensitive capabilitymemory_entity_resolveno sensitive capabilitymemory_episode_recallno sensitive capabilitymemory_episode_saveno sensitive capabilitymemory_explain_searchno sensitive capabilitymemory_exportno sensitive capabilitymemory_extract_sessionno sensitive capabilitymemory_forgetno sensitive capabilitymemory_graphno sensitive capabilitymemory_graph_indexno sensitive capabilitymemory_graph_statsno sensitive capabilitymemory_historyno sensitive capabilitymemory_observeno sensitive capabilitymemory_rebuild_embeddingsno sensitive capabilitymemory_rebuild_ftsno sensitive capabilitymemory_recallno sensitive capabilitymemory_recall_iterativeno sensitive capabilitymemory_reflect_nowno sensitive capabilitymemory_relateno sensitive capabilitymemory_saveno sensitive capabilitymemory_save_fastno sensitive capabilitymemory_search_by_tagno sensitive capabilitymemory_search_fastno sensitive capabilitymemory_self_assessno sensitive capabilitymemory_skill_getno sensitive capabilitymemory_skill_updateno sensitive capabilitymemory_statsno sensitive capabilitymemory_temporal_queryno sensitive capabilitymemory_updateno sensitive capabilitymemory_warmupno sensitive capabilitymemory_wiki_generateno sensitive capabilityphase_transitionno sensitive capabilityrule_set_phaseno sensitive capabilitysave_decisionno sensitive capabilitysave_intentno sensitive capabilitysearch_intentsno sensitive capabilityself_error_logno sensitive capabilityself_insightno sensitive capabilityself_patternsno sensitive capabilityself_reflectno sensitive capabilityself_rulesno sensitive capabilityself_rules_contextno sensitive capabilitysession_endno sensitive capabilitysession_initno sensitive capabilitytask_createno sensitive capabilitytask_phases_listno sensitive capabilityworkflow_learnno sensitive capabilityworkflow_predictno sensitive capabilityworkflow_trackno sensitive capabilityCross-tool combinations that form a data-exfiltration primitive (untrusted input → sensitive source → external sink).
Scan history per published version. The engine is deterministic — the same version always yields the same score, so a changed score means the package itself changed.
| Version | Score | Findings | Engine | Scanned |
|---|---|---|---|---|
v12.4.0 latest |
B 89/100 | 23 | 1.9.0 | 2026-07-23 |
Show this server's live Trust Score in your README, docs or website. The badge is served straight from the registry and updates automatically after every rescan — no API key needed. It links back to this page, so anyone who sees the grade can also read the findings behind it instead of taking a number on faith.
The score above is reproducible: the same package version always yields the same result. Run it locally or over the free API — no account, no LLM, fully deterministic.
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