Fibratus
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Security sensor for realtime threat detection and protection
fibratus run --filter "foreach(ps._ancestors, $a, $a.name = 'winword.exe')" fibratus rules list matches(file.extension, '*.exe') and imatches(process.name, 'cmd') not matches(dip.names, '10.0.0.0/8')
Summary
Fibratus is an open-source security sensor for Windows that watches system events in real time and matches them against a behavior-driven rule engine and YARA memory scanner to catch attacker tradecraft, malware, and other emerging threats. It runs as an agent installed on the endpoint itself, with events routed to output sinks or written to capture files for offline forensic analysis, and it can be extended with Python-based filaments for custom tooling. That places it in the hands of detection engineers and SOCSOCA security operations center, the team or function that monitors threats, investigates alerts and coordinates incident response. Its work can be internal, outsourced or shared. analysts who write and tune behavioral rules rather than rely solely on signature-based antivirus, and it ships with 50-plus curated detection rules covering privilege escalationprivilege escalationGaining permissions beyond those an account or process initially had. It can turn limited access into administrator control or access to another user's resources., defense evasion, and execution tactics out of the box. The project has been active since 2016 and shows sustained development, with 205 commits and 12 releases in the past year across a dozen contributors.
Security sensor for realtime threat detection and protection
How Fibratus helps
Which process on this endpoint just tried to escalate privileges or hide its tracks?
matches live process, image, and registry events against the shipped rule set covering privilege escalation, defense evasion, and execution tactics, and names the rule and offending process
Is malware hiding shellcode or an unbacked payload in a running process's memory?
scans process memory with YARA rules and flags regions matching known malicious patterns, tying the hit back to the responsible process
Did a process reach system calls directly to slip past hooked defenses?
watches for direct and indirect syscall invocation patterns that bypass normal API monitoring and raises a detection naming the technique
Which processes escalated using a token with elevated integrity or a different user context?
enriches process events with access token details such as integrity level and elevation type, so a rule can catch tokens that don't match the parent's privilege level
What actually happened on this host during an incident, step by step, after the fact?
writes the full event stream to a capture file that can be replayed and inspected offline, independent of whatever was visible at the time
Can I check whether a suspicious call chain came from a legitimate module or from injected code?
exposes callstack telemetry for memory and handle operations like allocation, process-open, and thread-open, so a rule can inspect the originating module and address for each frame
Languages
Command line
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Score card
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Shipping velocity releases a month, last 12 months
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Documentation quality release-notes rubric, 0–100
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Breaking-change discipline how rarely a release breaks users, and notice given
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Maintenance risk quiet time against its own cadence, maintainers
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Innovation & surface new capabilities, API and MCP surface
- Community health
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Contributor trend distinct committers, this year against last
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Maintainer concentration bus factor now against a year ago
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Issue backlog trend issues closed per issue opened, 12 months
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Responsiveness median time to a maintainer’s first reply
Nine scores for Fibratus, each built from the releases, notes and API history this site tracks — and, on Researcher and Business, where it stands among every measured tool in its category and how that has moved.
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Blank means never measured; nothing here is a filled-in zero.
Peer standings are included with Researcher and Business. See how this tool ranks against its competitors, using data we don't publish anywhere else.
See plans →Each score is 0–100 on a published rubric, derived from data this site already shows. A dimension we cannot measure says so — it is never scored 0 and never enters a rank.
How this is scored
- Shipping velocity — releases a month over the last 12 months, on a log scale where 16 a month scores 100. Needs 3 releases in the window.
- Documentation quality — the release-notes rubric published on the analytics page, unchanged.
- Breaking-change discipline — the share of releases carrying a breaking change (none scores 100, half or more scores 0). Only projects that label breaking changes are measured: a clean record cannot be told from an unlabelled one.
- Maintenance risk — quiet time measured against the tool's own release cadence (quiet longer than 90 days and three typical gaps scores 0), plus the number of active maintainers and whether contributors are growing, where known. Higher is lower risk.
- Innovation & surface — new capabilities in the feature ledger this year, API and MCP operations added, and the share of commits that are features: the mean of whichever we hold.
- Community health (open-source tools only) — each is a direction, not a size: contributors this year against last, the bus factor now against a year ago, and issues closed per issue opened, where steady scores 50, doubled 100 and halved 0; plus the median time to a maintainer's first reply (an hour scores about 100, a month or more 0). A commercial card has no repository and carries none of the four.
- Documented delivery (commercial tools) — when a vendor's documented new capabilities have slowed against its own baseline, that counts against the overall standing as heavily as two low dimensions. Steady delivery, or too little history to judge, leaves the standing alone; it is never a sixth score.
- Open-source tools are scored on repository signals; commercial tools on their published changelog. Ranks compare tools within one category and one profile and need at least five measured peers; the overall standing needs three ranked dimensions. Best-in-breed or consolidator is a shape, not a quality, and is never scored.
Release-note detail over time
See how much detail Fibratus puts in its release notes, quarter by quarter, and compare it with tracked tools in the same category. This history uses up to ten retained, reviewed notes per tool; sparse or blank older quarters may reflect that limit.
Checking release-note history…
Releases
17 entries
No entries match these filters.
- August 20261
- April 20261
- May 20251
- December 20241
- September 20242
- September 20231
- March 20231
- November 20221
- August 20221
- April 20221
- December 20211
- September 20211
- August 20211
- April 20211
- January 20171
- November 20161
Project health
Issue, contributor and maintainer activity in rabbitstack/fibratus, 2023-10 – 2026-09, as of 2026-09-25. Twelve-month figures first; the trend lines run the whole window.
- Contributors 1 −3 vs prior 12 months
- Maintainers 1 +0 joined · −0 left, last 12 months
- Bus factor 1 committers behind half the commits
- Community-filed 31% of issues opened, last 12 months
- Median time to close 3.4 days first maintainer reply 8.3 hours
- Open backlog 35 of 101 issues ever filed
- Issues opened / month 0 · 0 communitymaintainers
- Open backlog 35
- Contributors / month 1
- Commits / month 7
- Stars 2,547
- bugs 6%
- features 56%
- other 38%
Counts from the project's public repository and git history; no individuals are identified. Maintainers are the committers covering 80% of the last year's commits. how we measure this
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