tool-result-taint-py
Track untrusted tool output before it enters prompts or actions. Tag any value that came back from an LLM tool call as "tainted", carry that taint through your pipeline, and refuse to use it in a sensitive context until you've explicitly reviewed and unwrapped it. Zero runtime dependencies.
Python port of @mukundakatta/tool-result-taint.
Install
pip install tool-result-taint-py
Usage
from tool_result_taint import (
mark_tainted,
is_tainted,
taint_aware_dict,
taint_report,
unwrap_trusted,
)
# Wrap raw tool output before it enters your prompt-building pipeline.
result = mark_tainted("balance: $4321.00", source="bank.get_balance")
is_tainted(result) # True
result.value # "balance: $4321.00"
result.source # "bank.get_balance"
# Audit a batch of inputs (mix tainted + plain).
report = taint_report([result, "trusted-system-prompt"])
report.safe # False
report.tainted # [{"source": "bank.get_balance", "value": "..."}]
# Refuse to use a tainted value in a sensitive context.
try:
unwrap_trusted(result)
except RuntimeError:
pass # Caller must explicitly review or sanitize first.
unwrap_trusted("plain trusted string") # "plain trusted string"
# Wrap a dict so every entry is tainted automatically.
taint_aware_dict({"name": "Alice", "ssn": "XXX-XX-1234"}, source="crm.lookup")
# -> {"name": Tainted("Alice"), "ssn": Tainted("XXX-XX-1234")}
API
| Symbol | Behavior |
|---|---|
mark_tainted(value, source) |
Wraps value in a Tainted record stamped with source. |
is_tainted(value) |
True for any Tainted record (or dict with tainted=True). |
taint_aware_dict(mapping, source) |
Returns a new dict with each entry wrapped via mark_tainted. |
taint_report(inputs) |
Aggregates a list of inputs into TaintReport(safe, tainted). |
unwrap_trusted(value) |
Returns the raw value; raises if is_tainted(value). |
See the JS sibling's README for the full design notes.
1 maintainer
Metadata
1 maintainer
Release files for tool-result-taint-py 0.1.0
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