- Increased UI update interval from 350ms to 500ms
- Reduced dot animation frequency from 60ms to 250ms
- Reduced splash animation frequency from 50ms to 100ms
- Added content hash cache for rendered agent messages to avoid
re-parsing markdown and re-running Pygments on every tick
- Added guard to prevent redundant scroll_end callbacks from queuing
during rapid updates
Closes#581
StrixDockerSandboxClient.delete() best-effort-kills the sandbox container via
containers.get(id).kill() before delegating to the SDK's delete(), suppressing
docker NotFound/APIError. But when the docker daemon socket is already going
away — the normal case on a host/CI teardown — containers.get() ->
inspect_container raises requests' ConnectionError, which is a *sibling* of
docker.errors.APIError under requests.RequestException, not a subclass. So it
escapes the APIError-only suppress and surfaces a full traceback on teardown
even though the kill is meant to be best-effort.
Add RequestException to the suppress so the best-effort kill is genuinely
best-effort regardless of daemon reachability.
Test: tests/test_docker_client_delete.py — the kill raising ConnectionError
(and NotFound/APIError) is swallowed and delete() still delegates; unrelated
errors still propagate; no-container_id is a no-op. The ConnectionError case
fails against the pre-fix APIError-only suppress.
* feat: add bedrock + vertex optional extras with install docs and import hints (#574)
Declare [project.optional-dependencies] with vertex (google-auth) and
bedrock (boto3) extras so "strix-agent[vertex]" / "strix-agent[bedrock]"
install the provider SDKs. Add an Installation section to the Bedrock docs
mirroring Vertex, and a _provider_import_hint helper in warm_up_llm that
surfaces a pip-install hint when a provider dependency is missing.
Fixes#574, #573
* fix(providers): use pipx in install hint to match docs
A pipx-installed strix can't add an extra with 'pip install' (wrong env);
mirror the documented 'pipx install "strix-agent[...]"' command. Addresses
Greptile review.
Builds on the SARIF 2.1.0 emitter (#626): give each SARIF rule one or more
`stride:<leg>` tags (Spoofing / Tampering / Repudiation / Information
disclosure / Denial of service / Elevation of privilege) derived from the
finding's CWE, so consumers — the GitHub code-scanning Security tab, ASPM
dashboards, coverage reports — can group and filter findings by
threat-model leg. SARIF results inherit their rule's tags via ruleId, so
tagging the rule is sufficient.
- _CWE_TO_STRIDE maps common CWEs to legs (dominant leg first where a CWE
spans several); unmapped / no-CWE findings fall back to a default
(tampering + information-disclosure) so every finding carries >=1 leg
and downstream reports have no coverage gaps.
- Includes mappings for CWEs surfaced by real scans: 798 (hardcoded
creds), 862 (missing authz), 259 (hardcoded password), 1391 (weak
credential).
Tests: tests/report/test_sarif_stride.py (14 cases — mapping, normalization
of CWE-306/306/"cwe: 306" forms, default fallback, rule-tag emission).
_read_json_overrides is documented to let env vars outrank the
persisted cli-config.json, but it decided per-alias and broke on the
first alias found in either env or the file. When a multi-alias field
(e.g. api_key via LLM_API_KEY/OPENAI_API_KEY) was set in the env under
one alias but stored in the file under another, the stale file value
was surfaced as an init kwarg and overrode the live env var. A
lowercase env var was also missed (settings use case_sensitive=False).
Decide whether a field is already set in the environment by checking
all of its aliases case-insensitively before consulting the file. Add
regression tests for the cross-alias and case-insensitive cases.
Closes#688
* feat(report): SARIF 2.1.0 emitter for CI / code-scanning integration
Strix emits CSV + markdown + JSON but no SARIF, so findings can't feed
GitHub code-scanning, an ASPM, or any SARIF-consuming CI gate. Add a
stdlib-only emitter (strix/report/sarif.py) and always write findings.sarif
from ReportState._save_artifacts, beside the existing artifacts.
Design invariants (learned from running this in production):
- Stable partialFingerprints.primaryLocationLineHash per finding, so a
re-scan that re-words a title doesn't churn code-scanning alert IDs.
- Class/category hashing so the same vuln class maps to a stable ruleId
across scans rather than drifting.
- Findings with no code location anchor to SECURITY.md with a synthetic
location marker instead of being silently dropped.
- Always emit (even with zero findings) so a clean re-scan overwrites a
stale findings.sarif and code-scanning auto-resolves fixed alerts.
- tool.driver.version reports the strix package version.
- Fully isolated in its own try/except: a SARIF build error must never
break the CSV/MD/run-record path.
Verified end-to-end on v1.0.4 against a SQLi/cmd-inj/weak-hash fixture:
3 findings -> valid SARIF 2.1.0, 3 results, real code locations, distinct
per-finding fingerprints.
* fix(report): complete SARIF code scanning metadata
---------
Co-authored-by: bearsyankees <bearsyankees@gmail.com>
* Add five community security skills for agent specialization
Expand coverage with OAuth flow testing, AWS misconfigurations, prototype
pollution, insecure deserialization, and Django framework playbooks.
* Address Greptile review feedback on AWS and deserialization skills
- Use head-bucket for S3 existence checks instead of duplicating s3 ls
- Add Node.js to insecure_deserialization frontmatter description
* Clarify S3 existence vs public listing checks in aws skill
Split unauthenticated enumeration into separate head-bucket/HTTP
and s3 ls steps with interpretation guidance per review.
* some tools ads
---------
Co-authored-by: bearsyankees <bearsyankees@gmail.com>
Line 72 was over-indented, causing an IndentationError on import of strix/report/writer.py and breaking main. Also bump the mirrors-mypy pre-commit hook to v1.17.1 to avoid the mypy 1.16.0 internal crash (python/mypy#19412) on openai/_client.py.
* fix: resolve pre-commit check failures
- Change RuntimeError to TypeError for type validation in report/writer.py
- Update pyupgrade to v3.21.2 for Python 3.14 compatibility
* chore: add pytest test infrastructure
Mirror the layout introduced on feature/438-token_budget: pytest +
pytest-asyncio dev deps, asyncio_mode auto, a tests.* mypy override, and
pytest in the mypy pre-commit hook deps so the tests/ package type-checks.
* feat: add --mount and large-target pre-flight for local repos (#492)
Large local targets were copied into the sandbox file-by-file via the SDK
LocalDir entry, which stalls on big repos and could leave /workspace empty.
- --mount <path> bind-mounts a host directory read-only at /workspace/<subdir>
instead of copying it, bypassing the per-file stream.
- A size pre-flight (STRIX_MAX_LOCAL_COPY_MB, default 1024) fails fast with a
clear message suggesting --mount when a non-mounted local target is too big.
* fix: reject empty --mount paths
An empty or whitespace-only --mount value resolves to the current working
directory and would silently bind-mount it into the sandbox. Reject it.
* fix: dedupe local targets so a dir is never both copied and mounted
If the same directory is passed via --target and --mount (or as duplicate
values), it previously produced two targets — copied AND bind-mounted, and
the copied one could trip the size pre-flight. Dedupe by resolved path,
preferring the bind mount.
* fix: treat non-positive STRIX_MAX_LOCAL_COPY_MB as disabled
Previously a value of 0 (or negative) made every local target count as
oversized, aborting all local scans. Now <= 0 disables the pre-flight.
* fix: log unreadable subtrees during size pre-flight
os.walk silently swallowed directory-listing errors, so a permission-denied
subtree could make a large repo under-count and slip past the pre-flight.
Surface such omissions via an onerror warning.
* docs: document --mount and STRIX_MAX_LOCAL_COPY_MB
Add CLI reference + example for --mount, document the size pre-flight env var,
note the read-only-is-not-a-hard-boundary caveat and that remote repos are not
size-checked, and clarify the backends docstring on when bind mounts apply.
* Update strix/interface/main.py
* Update strix/runtime/docker_client.py
---------
* fix: resolve pre-commit check failures
- Change RuntimeError to TypeError for type validation in report/writer.py
- Update pyupgrade to v3.21.2 for Python 3.14 compatibility
* feat(cli): add --max-budget-usd flag
Raises BudgetExceededError in ReportUsageHooks after each LLM call when
accumulated cost reaches the limit, with clean "stopped" status and
child-agent cancellation in non-interactive mode.
* test: add budget enforcement unit tests
7 tests covering no-budget, under-budget, at-limit, over-limit, error
message content, None report state, and exception hierarchy.
Also adds pytest/pytest-asyncio to dev deps and a mypy override for tests.
* fix(budget): validate positive budget and check the live cost ledger
Two hardening fixes for --max-budget-usd enforcement:
- Reject non-positive budgets. ReportUsageHooks now raises ValueError for
max_budget_usd <= 0, and the CLI validates the flag via a custom argparse
type so '--max-budget-usd 0' fails fast with a friendly message instead of
silently killing the scan on the first model response.
- Read the live cost. The budget check now reads ReportState.get_total_llm_cost()
(the live ledger) instead of the persisted run-record snapshot, so it stays
accurate even when a usage save fails after a model call.
* fix(budget): stop the entire scan deterministically when the limit is hit
Previously a BudgetExceededError was handled per-agent: it was swallowed in
interactive mode (the loop kept waiting), a child's error escaped its detached
task as an unretrieved-exception warning, the parent was never released from
wait_for_message, and the stop was logged at ERROR with a traceback as if the
agent had failed.
Replace that with a single scan-wide signal on the coordinator:
- AgentCoordinator.trigger_budget_stop() sets a flag and wakes every parked
agent; wait_for_message returns as soon as the flag is set.
- The run loops check coordinator.budget_stopped and raise to exit cleanly,
marking themselves 'stopped'. The root's exception reaches run_strix_scan's
handler, which cancels descendants and tears the scan down once; child
exceptions are swallowed in their detached task.
- The budget stop is logged at INFO, not as a failure.
This is deterministic regardless of tree depth or which agent first sees the
limit, fixing the interactive/TUI hang where a deep agent's stop never reached
a parked root. Also re-raises BudgetExceededError explicitly in the stream
handler so it can't be mistaken for the LiteLLM 'after shutdown' race.
* fix(budget): treat a budget stop as a clean stop in the TUI
Add an explicit BudgetExceededError handler in the TUI scan thread so that, if
the error ever reaches it, the budget stop is logged as a graceful stop rather
than surfaced as a red scan error by the broad 'except Exception'. The runner
normally absorbs the error and returns cleanly, so this is defensive depth for
a money-spending feature.
* docs(cli): document --max-budget-usd behavior and limitations
Clarify that the budget is cumulative across all agents, checked after each
model response, that the scan stops cleanly (not as a failure), that the value
must be > 0, and that spend can slightly overshoot due to in-flight calls and
best-effort cost estimation.
* Apply suggestions from code review
---------
Register a litellm.success_callback that captures kwargs['response_cost']
into a new observed-cost bucket on LLMUsageLedger. record() skips the
tokens-times-registry estimate for LiteLLM-routed models so we do not
double-count with the callback; OpenAI direct routes keep estimating
since LiteLLM is not invoked for them. Per-agent attribution for
LiteLLM-routed calls is apportioned by token share at to_record() time.
OpenAI's Responses API rejects reasoning.effort on non-reasoning
models like gpt-4o with `unsupported_parameter`, so any scan with
the default STRIX_REASONING_EFFORT=high against gpt-4o crashed at
the first model call. drop_params=True absorbs the rejected param
on LiteLLM-routed models but the SDK's native OpenAI path has no
equivalent.
Lift model_supports_reasoning to a public helper that strips
litellm/, any-llm/, openai/ prefixes and falls back to last-segment
lookup so prefixed forms like anthropic/claude-opus-4-7 resolve
through the bare model_cost entry. make_model_settings regains
model_name and skips Reasoning() when the registry doesn't confirm
support. uses_chat_completions_tool_schema reuses the same helper
(was duplicating the lookup under a misleading name).
OpenAI's Responses API rejects tools[i].type="custom" on non-reasoning
models like gpt-4o (400 with code=unknown_parameter, param=tools).
Strix's SDK-native Filesystem capability registers CustomTool entries
by default, so a bare STRIX_LLM=gpt-4o run failed at the first tool
invocation even though warm-up (a tool-less call) succeeded.
uses_chat_completions_tool_schema now consults
litellm.model_cost[<name>].supports_reasoning for OpenAI routes and
flips to the chat-completions function-tool schema for models that
don't carry the reasoning flag. Same registry-lookup pattern as
is_known_openai_bare_model. Non-OpenAI prefixes and configs with
LLM_API_BASE are unchanged (still function tools).
