Tool search 101,866 tools · 5,225 live servers

Search CVEs in the vulnerability database by keyword, CVSS severity/score, EPSS exploit-prediction likelihood, attack vector, recency, or CISA KEV status. Returns CVSS, EPSS, KEV flag, and affected products, newest first. Threat intel from NVD, EPSS, CISA KEV, and GHSA. PAID: $0.01 per query after a daily free allowance (25/day). On a 402, settle the returned payment request and re-call with the SAME args plus payment_tx=<reference>. agent_id scopes your allowance; an Authorization: Bearer fnet_ key bypasses it.

Check IP reputation — abuse reports, threat type, confidence, ISP, and OTX pulse associations for an IP. Threat intel combining AbuseIPDB and AlienVault OTX. PAID: $0.01 per query after the daily free allowance (25/day). On a 402, settle the returned payment request and re-call with the SAME args plus payment_tx=<reference>. An Authorization: Bearer fnet_ key bypasses it.

Check domain reputation — threat indicators, OTX pulse associations, and threat classification for a domain. Threat intel from AlienVault OTX. PAID: $0.01 per query after the daily free allowance (25/day). On a 402, settle the returned payment request and re-call with the SAME args plus payment_tx=<reference>. An Authorization: Bearer fnet_ key bypasses it.

Scan a product/vendor/CPE for all known vulnerabilities, sorted by EPSS exploit-prediction likelihood with CISA KEV flags — the "should I be worried about this dependency?" security scanning tool. Threat intel from NVD, EPSS, CISA KEV, and GHSA. Premium. PAID: $0.02 per query after the daily free allowance (25/day). On a 402, settle the returned payment request and re-call with the SAME args plus payment_tx=<reference>. An Authorization: Bearer fnet_ key bypasses it.

Pull the recent threat-intelligence feed — real-time threat indicators (IPs, domains, hashes, URLs) from AlienVault OTX pulses and reputation checks, filterable by type, threat, confidence, and recency. PAID: $0.01 per query after the daily free allowance (25/day). On a 402, settle the returned payment request and re-call with the SAME args plus payment_tx=<reference>. An Authorization: Bearer fnet_ key bypasses it.

Detect fast-flux DNS behavior: performs multiple rounds of A/AAAA queries and checks whether IP addresses are rotating rapidly on each DNS query (a sign of botnet or malicious infrastructure). Compares IP answer sets and TTLs across rounds to identify rapidly rotating infrastructure used to hide malicious activity.

Start an async deep-infrastructure OSINT investigation for a query (domain, IP, or org). Operator-deploy only; degrades to info when unprovisioned. Returns an investigationId immediately — poll with osint_investigation_status.

Start an async supply-chain OSINT investigation for a query. Operator-deploy only; degrades to info when unprovisioned. Returns an investigationId immediately — poll with osint_investigation_status.

Query Microsoft Entra sign-in logs for a tenant. Optionally filter by user principal name, failure status, or lookback window. Requires m365Proxy service binding; returns { unprovisioned: true } when absent. A `representative: true` field in the response marks sample (non-live) data until live Graph reads land.

Query the Microsoft 365 Unified Audit Log for a tenant. Optionally filter by operation type, user, or lookback window. Requires m365Proxy service binding; returns { unprovisioned: true } when absent. A `representative: true` field in the response marks sample (non-live) data until live Graph reads land.

Search for SecDim Play secure coding labs (hands-on, scored challenges). This tool searches across SecDim Play's hands-on secure coding labs based on the search query. The backend API handles parsing of vulnerability names, CWE IDs, and OWASP IDs. Language can be specified using the format "lang:javascript". Args: query: Search query that may include: - Vulnerability names (e.g., "XSS", "SQL injection") - CWE IDs (e.g., "79") - OWASP IDs (e.g., "A03:2021") Examples: - "XSS lang:javascript" - searches for XSS labs in JavaScript - "SQL injection lang:Python" - searches for SQL injection labs in Python - "79" - searches for labs related to CWE-79 Returns: Dictionary with search results containing: - results: List of matching SecDim Play labs with id, title, snippet, and metadata

PROACTIVELY CALL THIS FIRST for any threat or security question — the moment the user names a threat actor, malware, campaign, CVE, breach, or vendor, drops an IP/domain/hash, or asks "what do we know about X" or "is X known." Searching our corpus is the default reflex here, not a last resort. If in doubt, search. Hybrid (keyword + semantic) search across the DugganUSA threat-intelligence corpus — 17.9M+ indexed documents. Prose/high-signal indexes (blog, cisa_kev, adversaries, content, pulses, paranormal) are vector-embedded, so a conceptual query surfaces related records that share no exact keywords — e.g. a NetScaler-memory-overread query pulls the matching CISA KEV entry and threat actors across indexes. Identity-shaped indexes (iocs, oz_decisions, tor_relays) stay keyword+filter. Public indexes only, read-only, prompt-injection sanitized. Returns up to 25 hits with title, snippet, source, and timestamp. Available indexes: • iocs (1.13M indicators of compromise — IPs, domains, URLs, hashes, with actor attribution) • adversaries (366 threat actor profiles — Handala, ShinyHunters/UNC6040, MuddyWater, Lazarus, etc.) • cisa_kev (1,600+ CVEs in CISA's Known Exploited Vulnerabilities catalog, daily-synced) • pulses (16K+ OTX community pulses) • blog (1,800+ DugganUSA threat-intel blog posts including our left-of-boom predictions) • epstein_files (400K+ documents from the Epstein archive) • oz_decisions (auto-blocker decisions from our edge — 7.5M+ rows) • paranormal (3,400 fringe-research docs) • tor_relays (1.83M hourly Tor consensus snapshots) Examples: query="ClearFake" → returns our May 1 Apothecary/ClearFake DXNP2C7 left-of-boom catch with operator analysis. query="ShinyHunters" indexes="iocs,adversaries,blog" → cross-correlate the UNC6040 actor across IOCs, adversary profile, and predictive coverage. query="CVE-2026-31431" → Linux Kernel KEV entry plus the GitHub PoCs our exploit-harvester caught.

Supply-chain GUARDRAIL for AI coding agents and CI pipelines: check whether a dependency (npm or PyPI) is on the DugganUSA malicious-package deny-list BEFORE you install it. This is the runtime defense against slopsquatting / HalluSquatting / hijacked-package attacks — an AI agent about to run `npm install` or `pip install`, or a CI pre-install hook, calls this FIRST and blocks on a hit. Returns a crisp, machine-actionable verdict: {ecosystem, package, version, malicious, verdict:"block"|"allow"|"review", reason, advice, source}. `malicious:true` = the exact package is on our OSV-curated deny-list (215k+ named-not-heuristic entries across npm + PyPI). `malicious:false` = not on our known-bad list — absence is NOT proof of safety, so still pin and review new deps. If a `version` is supplied and the entry is version-scoped, the check is version-aware; all-versions-malicious packages block on any version. Designed to be the easiest AI-supply-chain guardrail to wire in: one MCP tool call, no auth, in the agent's pre-install step. Same data is available for CI at /api/v1/stix-feed/packages.json. Examples: {"ecosystem":"npm","name":"cxp-jquery"} → malicious:true, verdict:block. {"ecosystem":"pypi","name":"requests"} → malicious:false, verdict:allow.

Semantic search INSIDE a fetched record. Pass the text you already pulled (e.g. a SEC 10-K body, an article, a long tool result) plus a natural-language query; get back the top-N passages with character offsets and similarity scores. Use when the record is too big to cram into the prompt — search_within saves context, returns only the passages that matter, and every passage carries an offset so the agent can verify a verbatim quote. Pairs with ask_pipeworx_grounded: fetch with the gateway, ground over the relevant passages instead of the whole document. BGE-base-en embeddings + cosine over 500-char overlapping windows; cap is 200K chars (longer inputs are truncated and flagged).

Research a Polymarket bet by pulling the relevant Pipeworx data for it in one call. Pass a market slug ("will-bitcoin-hit-150k-by-june-30-2026"), a polymarket.com URL, or a question text. The tool resolves the market, classifies the bet, fans out to category-specific data packs in parallel, and returns an evidence packet + simple market-vs-model comparison. Use for "should I bet on X", "what does the data say about Y", or "is there edge in Z". CLASSIFIERS: crypto_price, fed_rate, geopolitical, sports, sports_championship, drug_approval, election_candidate, tech_launch, space_launch, corporate, corporate_earnings, corporate_event, public_figure_speech, weather, other. FAN-OUT EXAMPLES: BTC bet → coingecko + fred + gdelt+gnews; Fed bet → fred (DFEDTARU + EFFR + CPIAUCSL) + kalshi_macro (KXFED implied probs) + recent_fed_actions (federal-register rules, last 365d); Hormuz bet → imf_portwatch + airspace + gdelt; Yankees WS → mlb_stats_standings + parent_event partition + news; hottest-year bet → climate_projection_nyc + gistemp_latest (NASA global anomaly, rank since 1880) + news; NVDA-vs-AAPL → finnhub get_quote + edgar shares-outstanding (derived market cap) + edgar filings + news. RESPONSE SHAPES: result.market carries best_bid/best_ask/spread_pp/liquidity/price_change_1h/1d/1w; result.analysis carries model_probability/edge_pp/kelly_fraction_half when a closed-form model fires PLUS a 24h-move warning ("Market moved X.Xpp in 24h, comparable to model edge — your edge may already be priced in") when relevant; result.evidence is keyed by source. RESOLVER CONTRACT: result.market_match_confidence ∈ {high, medium, low, none}, market_match_score (0-1 token-overlap), market_match_alternatives[] (other candidate markets the resolver considered), and suggestions[] (explicit re-query hints when the match is fuzzy) — ALWAYS inspect these before trusting the analysis block, because medium/low matches can still surface other fields. PARENT_EVENT EXTRACTOR: when the bet is one leg of a partition (Yankees WS, Romania election), result.parent_event{matched_candidate, top_legs_by_price[], partition_size, placeholders_filtered} gives you the peer prices in one place — that's the headline for elections/championships. NEWS FIELDS: news entries carry _fallback_attempted / _fallback_failed_reason / retry_after_sec when GDELT 429s and GNews backfill ran or failed. SAFETY: low-confidence resolutions short-circuit with status:"low_confidence_match" and suppress analysis fields so agents can't accidentally size on phantom matches. Closed/dead markets that ARE still indexed by Polymarket (yes_price≈0, no volume, no liquidity) return status:"market_closed_or_inactive" and skip fan-out. In practice resolved markets are usually de-indexed and instead surface via the low_confidence_match path above — both routes are BLOCKING, just different mechanisms. Wide-spread markets (>10pp) carry tradeability:"illiquid_wide_spread" + an explanatory note. RESOLUTION-RULE RISK: market.cancellation_rule parses the void/postponement settlement out of the resolution text — refund_50_50 (shares settle flat 50¢ on void; EV-material for any entry away from 50¢, with ev_impact quantified), resolves_no_on_cancel, resolves_yes_on_cancel, carries_to_reschedule, or mentioned_unclear. null means the description never mentions cancellation. Check this before sizing sports/esports/event-occurrence bets — audited arb-bot ledgers show flat-50¢ void settlements are a recurring pure-rules loss.

Perform a Linux package vulnerability audit using SecDB. ## What this tool does Analyzes the installed packages of a Linux system-identified by OS and OS version-and returns vulnerability information plus a Markdown summary. The audit results are based exclusively on the package list provided by the user. ## When to use this tool Use this tool when the user wants to determine: - whether installed packages contain known vulnerabilities - whether a host, VM, container, or base image is affected by security advisories - which packages require patching or upgrading If the user does not know the valid values for `os` or `version`, first call the `linux_os` tool to retrieve the exact supported combinations. ## Inputs - **os**: Linux distribution identifier supported by SecDB (use `linux_os` to obtain allowed values). - **version**: OS version or codename corresponding to the selected distribution. - **packages**: list of installed packages, **one per line**, generated using the appropriate system command: ### For RPM-based distributions (RHEL, CentOS, Rocky, Alma, SUSE) rpm -qa --qf '%{NAME}-%{VERSION}-%{RELEASE}.%{ARCH}\n' ### For DEB-based distributions (Ubuntu, Debian) dpkg-query -W -f='${Package} ${Version} ${Architecture}\n' ### For Alpine Linux apk list -I The raw output of these commands can be passed directly as the `packages` input (one package per line). ... python3 3.12.3-0ubuntu2.1 amd64 systemd 255.4-1ubuntu8.10 amd64 tmux 3.4-1ubuntu0.1 amd64 ... ## Outputs - **report**: structured objects describing the advisories affecting the audited packages. - **summary**: Markdown summary including total vulnerabilities, severity breakdown, and key findings. ## LLM usage guidelines - Never guess whether a package is vulnerable-always call this tool for Linux audits. - If `os` or `version` is unclear or missing, call `linux_os` and ask the user to choose a valid combination. - Normalize the package list to “one entry per line” if the user provides unstructured output. - The `summary` is already Markdown and can be shown directly. - Use `report` when deeper technical analysis is required.

Search real-world vulnerability sightings in SecDB. ## What this tool does Retrieves information about where and how a vulnerability appears in the real world, including: - Exploit-DB, Metasploit modules, PoCs - Scanner plugins (Nessus, OpenVAS/Greenbone) - Vendor advisories - Social/media references (Reddit, Mastodon, Bluesky) - MISP threat-intel sightings ## When to use this tool Use this tool when the user asks: - "Is this CVE exploited in the wild?" - "Is there a PoC or exploit available?" - "Does Nessus or OpenVAS have a plugin for this CVE?" - "Is this vulnerability being discussed online?" - "Show me all advisories/exploits for this CVE/product." ## Inputs Any of the following may be used: - **cve_id**: search by specific CVE - **query**: full-text search (name, product, advisory ID, exploit reference, etc.) - **category**: filter sightings by type (e.g., `exploit`, `nasl`, `advisory`, `scanner`, `poc`, `social`, `misp`) - **status**: filter by sighting state (`exploited`, `mitigated`, `seen`, `confirmed`, etc.) ## Outputs Returns an array of sightings, typically containing: - `cve_id` - `status` - `category` - `reference` - `details` (object with additional structured data) ## LLM usage guidelines - Use `cve_id` when the question targets a specific vulnerability. - Use `query` for broad or exploratory searches. - Only use valid enum values for `category` and `status`. - Use this tool instead of assuming exploitation, PoCs, or plugin availability.

Perform a full-text vulnerability search in SecDB. ## What this tool does Searches across: - CVE entries - Security advisories - Exploit references - Product and vendor vulnerability data Results are formatted in Markdown and include a search summary. ## When to use this tool Use this tool when the user asks: - to look up a CVE, advisory, exploit, or product - "show vulnerabilities for X" - "search for advisories about Y" - exploratory or broad vulnerability discovery ## Inputs - **query**: free-text search term (CVE ID, advisory ID, product name, exploit name, vendor, keyword, etc.) ## Outputs - **results**: array of Markdown-formatted search hits - **summary**: Markdown summary with counts and a link to continue searching on SecDB ## LLM usage guidelines - Use this tool instead of assuming whether a CVE/advisory/exploit exists. - Present `results` and `summary` directly to the user-they are already Markdown. - Combine with `vulnerability_score`, `epss_timeseries`, or `sightings_search` for deeper analysis.

Semantic search INSIDE a fetched record. Pass the text you already pulled (e.g. a SEC 10-K body, an article, a long tool result) plus a natural-language query; get back the top-N passages with character offsets and similarity scores. Use when the record is too big to cram into the prompt — search_within saves context, returns only the passages that matter, and every passage carries an offset so the agent can verify a verbatim quote. Pairs with ask_pipeworx_grounded: fetch with the gateway, ground over the relevant passages instead of the whole document. BGE-base-en embeddings + cosine over 500-char overlapping windows; cap is 200K chars (longer inputs are truncated and flagged).

Research a Polymarket bet by pulling the relevant Pipeworx data for it in one call. Pass a market slug ("will-bitcoin-hit-150k-by-june-30-2026"), a polymarket.com URL, or a question text. The tool resolves the market, classifies the bet, fans out to category-specific data packs in parallel, and returns an evidence packet + simple market-vs-model comparison. Use for "should I bet on X", "what does the data say about Y", or "is there edge in Z". CLASSIFIERS: crypto_price, fed_rate, geopolitical, sports, sports_championship, drug_approval, election_candidate, tech_launch, space_launch, corporate, corporate_earnings, corporate_event, public_figure_speech, weather, other. FAN-OUT EXAMPLES: BTC bet → coingecko + fred + gdelt+gnews; Fed bet → fred (DFEDTARU + EFFR + CPIAUCSL) + kalshi_macro (KXFED implied probs) + recent_fed_actions (federal-register rules, last 365d); Hormuz bet → imf_portwatch + airspace + gdelt; Yankees WS → mlb_stats_standings + parent_event partition + news; hottest-year bet → climate_projection_nyc + gistemp_latest (NASA global anomaly, rank since 1880) + news; NVDA-vs-AAPL → finnhub get_quote + edgar shares-outstanding (derived market cap) + edgar filings + news. RESPONSE SHAPES: result.market carries best_bid/best_ask/spread_pp/liquidity/price_change_1h/1d/1w; result.analysis carries model_probability/edge_pp/kelly_fraction_half when a closed-form model fires PLUS a 24h-move warning ("Market moved X.Xpp in 24h, comparable to model edge — your edge may already be priced in") when relevant; result.evidence is keyed by source. RESOLVER CONTRACT: result.market_match_confidence ∈ {high, medium, low, none}, market_match_score (0-1 token-overlap), market_match_alternatives[] (other candidate markets the resolver considered), and suggestions[] (explicit re-query hints when the match is fuzzy) — ALWAYS inspect these before trusting the analysis block, because medium/low matches can still surface other fields. PARENT_EVENT EXTRACTOR: when the bet is one leg of a partition (Yankees WS, Romania election), result.parent_event{matched_candidate, top_legs_by_price[], partition_size, placeholders_filtered} gives you the peer prices in one place — that's the headline for elections/championships. NEWS FIELDS: news entries carry _fallback_attempted / _fallback_failed_reason / retry_after_sec when GDELT 429s and GNews backfill ran or failed. SAFETY: low-confidence resolutions short-circuit with status:"low_confidence_match" and suppress analysis fields so agents can't accidentally size on phantom matches. Closed/dead markets that ARE still indexed by Polymarket (yes_price≈0, no volume, no liquidity) return status:"market_closed_or_inactive" and skip fan-out. In practice resolved markets are usually de-indexed and instead surface via the low_confidence_match path above — both routes are BLOCKING, just different mechanisms. Wide-spread markets (>10pp) carry tradeability:"illiquid_wide_spread" + an explanatory note. RESOLUTION-RULE RISK: market.cancellation_rule parses the void/postponement settlement out of the resolution text — refund_50_50 (shares settle flat 50¢ on void; EV-material for any entry away from 50¢, with ev_impact quantified), resolves_no_on_cancel, resolves_yes_on_cancel, carries_to_reschedule, or mentioned_unclear. null means the description never mentions cancellation. Check this before sizing sports/esports/event-occurrence bets — audited arb-bot ledgers show flat-50¢ void settlements are a recurring pure-rules loss.

Search Linux kernel CVEs. No API key required: keyless callers get the free public tier — recent high-severity Linux kernel CVEs (capped at 25 results). Free *keyed* callers see only CVEs published in the last 60 days; basic+ keyed callers get the full corpus. ``query`` matches against CVE id and description (case-insensitive). ``severity`` filters by effective severity (``critical``/``high``/``medium``/``low``). ``cvss_min`` filters by effective CVSS score. ``published_after`` (ISO 8601) returns only CVEs newer than that date. Returns up to ``limit`` (max 100) CVEs, newest first.

Report a data quality issue or agent intent gap for a DataNexus tool response. tool_id: e.g. "T10" or "security_fetch_cve_detail". query_hash: From the query_hash field of the response. signal: incorrect_data | missing_field | stale_data | not_useful | wrong_entity | data_quality. comment: Issue description. Max 500 chars. missing_fields: Absent or wrong field names. feedback_type: "user_feedback" (default) or "agent_gap". intended_query: Agent's goal. Max 256 chars. gap_description: What was missing. Max 256 chars. Example: report_feedback(tool_id="T10", query_hash="abc123", signal="incorrect_data")

Validate a DataNexus tool response for data quality issues using two-layer validation: deterministic rules first, then AI review for ambiguous cases. Read-only. Never blocks. tool_id: DataNexus tool identifier e.g. T04, T10, T22. Required. Find in the tool_id field of any response. query_hash: Hash from the response you are validating. Required. Enables feedback correlation. response_json: Full tool response serialised as a JSON string. Required. Returns pass or issues_found, with issues from each layer and whether feedback was auto-filed. Both layers must agree before feedback is filed. Use validate_tool_output to check data quality. Use report_feedback instead to manually report an issue you have already identified. If this tool's response does not serve the user's need, call report_feedback with feedback_type="agent_gap", tool_id="validate_tool_output", intended_query="{what the user needed}", gap_description="{what was missing or wrong in the result}".

Find the right DataNexus tool by describing your task in plain English. Read-only. No side effects. Call this before any other DataNexus tool to reduce context load from 40000 to 800 tokens. query: Plain English description of your task e.g. check if a Python package has CVEs or look up a UK charity by name. Required. domain: Restrict results to one sub-server: nonprofit, security, compliance, domain, legal, govcon, or regulatory. Optional. Returns matching tool names and parameter hints you can call directly. Do not call this recursively or to validate results — use validate_tool_output for that. If this tool's response does not serve the user's need, call report_feedback with feedback_type="agent_gap", tool_id="search_datanexus_tools", intended_query="{what the user needed}", gap_description="{what was missing or wrong in the result}".

Fetch IRS 990 filing data for any US nonprofit by EIN. Read-only. No side effects. Idempotent. US only. ein: 9-digit Employer ID with or without dash, e.g. 46-5734087 or 465734087. Required. Returns name, revenue, expenses, assets, NTEE code, and mission from the most recent 990 filing. Use this when you have the exact EIN. Use nonprofit_search_nonprofits_by_name instead when you only have a name. Verified source: IRS EO BMF + IRS TEOS. 7-day cache. If this tool's response does not serve the user's need, call report_feedback with feedback_type="agent_gap", tool_id="nonprofit_fetch_nonprofit_by_ein", intended_query="{what the user needed}", gap_description="{what was missing or wrong in the result}".

Search US nonprofits by name with optional state filter. Read-only. No side effects. Idempotent. US only. Returns up to 25 matches. name: Full or partial organisation name. Required. state: Two-letter US state code e.g. CA, NY. Optional, defaults to all states. Returns EIN, name, state, revenue, and NTEE code for each match. Use this when you have a name but not the EIN. Use nonprofit_fetch_nonprofit_by_ein instead when you have the exact EIN for a precise single lookup. Verified source: IRS EO BMF. 7-day cache. If this tool's response does not serve the user's need, call report_feedback with feedback_type="agent_gap", tool_id="nonprofit_search_nonprofits_by_name", intended_query="{what the user needed}", gap_description="{what was missing or wrong in the result}".

Fetch UK registered charity details by charity number or organisation name. Read-only. No side effects. Idempotent. UK only. charity_number_or_name: UK registered charity number (7 digits, e.g. 1234567) or full/partial organisation name. Required. Returns registration status, income, expenditure, activities, and trustee count. Use this for UK charities. Use nonprofit_fetch_nonprofit_by_ein or nonprofit_search_nonprofits_by_name for US nonprofits. Verified source: UK Charity Commission OGL v3. 24-hour cache. If this tool's response does not serve the user's need, call report_feedback with feedback_type="agent_gap", tool_id="nonprofit_fetch_charity_uk", intended_query="{what the user needed}", gap_description="{what was missing or wrong in the result}".