Claude models are served on /messages, which the OpenAI SDK can't speak, so
those runs go through LiteLLM's Anthropic route instead. Prompt caching moves
with them, since LiteLLM consumes the injection points the raw SDK rejects.
Zen and Go now show up by name instead of both reading 'OpenCode
subscription', and Zen keeps its cost tracked: it bills prepaid credits per
request, so those runs were never actually free.
* fix(report): neutralize CSV formula injection in vulnerabilities.csv
write_vulnerabilities() wrote finding titles straight into vulnerabilities.csv.
The csv module escapes CSV syntax but has no notion of spreadsheet formula
triggers, so a title beginning with =, +, -, @, tab or CR reached the cell
intact and was evaluated when a human opened the file (CWE-1236).
That input is attacker-influenced by design: Strix scans untrusted targets and
the agent quotes target content verbatim into finding titles, so a scanned page
can dictate a cell's literal contents. _validate_required_text only checks the
title is non-blank.
Add csv_safe() and apply it to every cell written. A value starting with a
formula trigger is prefixed with an apostrophe, the standard mitigation:
spreadsheets render the rest as literal text and hide the apostrophe.
This follows the module's existing safe_fence() precedent, which already guards
the markdown path against the same class of attacker-influenced content.
Adds regression tests covering the six trigger characters, that the payload
survives intact behind the guard, and that benign titles are untouched.
* report: single-line titles, exact CSV bytes, accurate csv_safe docstring
Strip control characters from finding titles at the ReportState choke point so
the guard in the CSV writer is defense-in-depth rather than the only layer, and
write artifacts with newline="" so the CSV's own \r\n terminators are not
rewritten to \r\r\n on Windows.
* report: normalize hydrated titles on resume
* report: rewrite finding markdown when resume cleans its title
---------
Co-authored-by: itzzdev09 <devved90@gmail.com>
* add a generic MCP client and a config for connecting MCP servers
* Add MCP docs and CLI polish: docs page, startup connect summary, --mcp-config flag, compact tool output
* Add MCP connection notes and per-run selection; clean up on cancel and dedupe names
* Show errored MCP tool calls as failed in the TUI
* Sanitize namespaced tool names so model APIs accept them
* Show MCP tool calls distinctly in the terminal and the run viewer
* Say what MCP servers are worth connecting for
* Correct the notes docstring to match how notes reach the agent
* keep the mcp tests from reading your shell's STRIX_MCP_* vars
Treat tool_output_max_tokens as a ceiling so an explicit model-supplied
cap can't exceed it, and derive the truncation notice's dropped-line
count from the lines actually kept after the byte-trim pass. Also cast
the pygments fallback lexer so it satisfies the resolve_lexer return
type under the pre-commit mypy hook.
* fix(report): prevent code-fence breakout in vulnerability markdown
render_vulnerability_md wrapped LLM-authored poc_script_code and code
snippet values in a fixed three-backtick fence, so a triple-backtick inside
the value closed the fence early and the rest rendered as live markdown
(headings, tracking-beacon images) in the shareable report deliverable.
Open each such block with a fence one backtick longer than the longest
backtick run in the payload (CommonMark: a block closes only on a fence at
least as long as the opener), so the content always renders verbatim. The
adjacent ```diff block is already safe (its lines are '- '/'+ ' prefixed and
so can never be a bare-backtick closing fence) and is left unchanged.
Fixes#815
* fix(report): indent multiline snippets
---------
Co-authored-by: thejesh23 <thejesh23@users.noreply.github.com>
Co-authored-by: Alex Schapiro <bearsyankees@gmail.com>
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).
Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com>
* 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.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* fix(report): complete SARIF code scanning metadata
---------
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
* 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
Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>
---------
Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>
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.
Drop every hand-rolled provider table and per-model gating that had
accumulated in the model-handling layer:
* normalize_model_name no longer auto-prefixes bare claude-* / gemini-*
names. Users supply the full <provider>/<model> form. The function
became literally model_name.strip(), so callers now inline that and
the function is removed.
* tool_choice="required" is gone everywhere. Thinking-mode endpoints
(Anthropic, DeepSeek /beta) reject it; modern reasoning models don't
need it; non-interactive runs already have
_append_noninteractive_tool_required_message as the convergence
backstop. model_supports_reasoning, model_known_to_registry, and
_model_cost_entry were only used to gate this and follow it out.
* Reasoning(effort=...) is now attached whenever
STRIX_REASONING_EFFORT is non-none. litellm.drop_params=True absorbs
it for non-reasoning models.
* Warm-up's bare-name OpenAI 401 hint is removed (false-positive prone,
relied on substring matching).
* reset_tool_choice on SandboxAgent is no-op now (no tool_choice gets
set) and is removed.
* report/dedupe.py was still routing through stock MultiProvider, so
non-OpenAI configs failed the dedupe LLM pass; switch it to
StrixProvider.
Verified end-to-end against modern provider strings (openai/gpt-5.4,
anthropic/claude-opus-4-7, deepseek/deepseek-reasoner,
gemini/gemini-2.5-pro, groq/, xai/, mistral/, together_ai/, perplexity/,
openrouter/, litellm/ legacy form, and whitespace-padded input): 18/18
cases route correctly, env vars mirror via litellm.validate_environment,
and ModelSettings carries no tool_choice. mypy strict passes.
Both backends share session/version/first-run helpers in
strix/telemetry/_common.py and fire from the same four call sites in
strix/interface/main.py and strix/report/state.py. STRIX_TELEMETRY is
the single toggle for both.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
Jonathan Singer