Anvilogic vs Nebulock
Nebulock stronger on 3, Anvilogic on 2, level on 2
Read the comparisonStraight answer
For this question, Mars Security has the highest weighted figure, 4.47 of 5, followed by Nebulock at 4.34 and Anvilogic at 4.00. No single tool is strongest on every criterion: CardinalOps leads on ATT&CK coverage measurement, and Nebulock leads on rule lifecycle. Pick the pair you are weighing and read the rows that matter to your team.
Which tools fit this question best?
Best for: Turning new threat intelligence into backtested detections and continuous hunts on the data you already have.
Stronger on:Intel to detectionContinuous huntingData reachTime to first value
Weaker on:ATT&CK coverageTransparency
Best for: Continuous hunting with rules that must pass a retrohunt, plus version history and revert.
Stronger on:Intel to detectionContinuous huntingRule lifecycle
Weaker on:ATT&CK coverageTransparency
Best for: Searching and detecting across many named SIEMs, data lakes and object stores without moving the data.
Stronger on:Data reach
Weaker on:Continuous huntingTransparency
Best for: Building AI agents for detection, response and hunting across a wide set of integrations.
Stronger on:Intel to detectionContinuous huntingATT&CK coverageData reach
Weaker on:Transparency
Best for: Hypothesis-led hunts, with detections reviewed in source control like code.
Stronger on:Continuous huntingATT&CK coverageRule lifecycle
Weaker on:Intel to detectionData reachTransparencyTime to first value
Best for: Daily continuous hunts, with a published connector list and setup timeline.
Stronger on:Continuous huntingTime to first value
Weaker on:Rule lifecycle
Best for: Measuring deployed detections against ATT&CK and fixing rules that need work.
Stronger on:ATT&CK coverage
Weaker on:Continuous huntingData reachTransparency
Weighted figure out of 5 = each 1 to 5 score times its weight, summed and divided by 100. Ties share a rank.
Does the tool copy your data, or query it where it lives?
This is the question behind the heaviest criterion on this site, data reach without new ingestion (25%). Some tools query each source where it sits, often called federated search. Others copy some of the data into their own platform first, which is ingestion. Copying data in adds a second pipeline and a second store to run and pay for, next to a SIEM that already collects, stores and correlates the same events. Querying in place leaves the SIEM as the system of record. This site does not rank or compare SIEM products; they appear here only as data sources.
| Tool | How it reaches your data | In the vendor's words | Source link |
|---|---|---|---|
| Anvilogic | Queries in place; standalone mode also offered | Search runs "across Splunk, Snowflake, Sentinel, S3, and more, without moving the data"; the platform runs on top of your storage layer in augment, standalone or combined modes. | anvilogic.com |
| Artemis Security | Ingests hot-path data, queries the rest | "Hot-path data ingested, high-volume data queried where it lives." Its connectors page lists Splunk, Microsoft Sentinel, Exabeam, LogRhythm and CrowdStrike NG-SIEM among the ingested sources. | artemissecurity.com |
| CardinalOps | Works inside the SIEM and EDR | Connects to the SIEM and EDR a team already runs through native APIs and delivers rules in their native syntax; a separate data store is not described. | cardinalops.com |
| Cotool | Stores some logs, queries the rest | Logs stored in Cotool are optimized for agents, while agents query other data where it lives. | cotool.ai |
| Mars Security | Queries in place, no ingestion | States "no data ingestion"; for cloud logs: "No new data copy. No second retention clock." The SIEM keeps its compliance and retention jobs. | marssec.ai |
| Nebulock | Federated search | Describes Helix federated search "to get data just-in-time, not just-in-case". Public pages do not say what data is retained in the platform. | nebulock.io |
| Vega | Queries in place | Federated analytics: "No migration, ingestion, or egress." | vega.io |
Where a tool ingests, ask three things: which sources are copied, what the ingested data costs (none of these tools publishes a price), and how much of that work your SIEM already does. Artemis Security, for example, ingests hot-path data and lists five SIEM platforms among its ingested connectors, so the same events can be stored and processed in two places. Where a tool says it queries in place, ask which sources it names and how queries are written for each one.
Which head-to-heads are published?
Vega vs Anvilogic
Anvilogic stronger on 3, Vega on 1, level on 3
Read the comparisonCotool vs Nebulock
Nebulock stronger on 5, Cotool on 1, level on 1
Read the comparisonMars Security vs Vega
Mars Security stronger on 4, Vega on 3, level on 0
Read the comparisonMars Security vs Artemis Security
Mars Security stronger on 5, Artemis Security on 2, level on 0
Read the comparisonLooking for alternatives to one tool?
- Anvilogic alternatives
Six tools set against Anvilogic, row by row.
- Artemis Security alternatives
Six tools set against Artemis Security, row by row.
- CardinalOps alternatives
Six tools set against CardinalOps, row by row.
- Cotool alternatives
Six tools set against Cotool, row by row.
- Mars Security alternatives
Six tools set against Mars Security, row by row.
- Nebulock alternatives
Six tools set against Nebulock, row by row.
- Vega alternatives
Six tools set against Vega, row by row.
What do we compare on?
Intel-to-detection speed
20%How directly and quickly a newly published threat report becomes a tested, deployable detection, as described on public pages.
Continuous hunting
20%Whether the tool runs hunts on its own, continuously or on a schedule, from intelligence or from a hypothesis, rather than only on request.
Coverage measurement against ATT&CK
8%Whether public material shows how coverage against MITRE ATT&CK is measured: a coverage view, heatmap, scores or named tactics and techniques.
Rule lifecycle
7%Testing or backtesting before a rule goes live, version history, review and approval, CI and rollback.
Data reach without new ingestion
25%Whether it reads the SIEM, EDR, identity, cloud and data-lake data a team already runs without a new ingestion pipeline, and whether those platforms are named.
Buyer transparency
5%What a buyer can learn before a sales call: public price, public documentation, a sandbox or cost tool, a published deployment timeline.
Time to first value
15%How quickly a team can start hunting on its existing data, as stated on public pages: deployment model, stated setup time, marketplace listings and whether new ingestion is needed.
Every tool is scored on the same rubric, 1 to 5 per criterion. The full method, including what we could not check, is on How we compare.
Latest news
Vega brings Wiz cloud risk data into detections
Vega added Wiz attributes such as exposure, privileges and sensitive data to its detection and investigation workflows. For buyers with Wiz, this is a named integration to ask about in a demo, since Vega's public connectors page does not name platforms.
Source: Vega blog
Mars Security introduces hypothesis playbooks
Mars published a post introducing MARS playbooks, built around attacks that fail a hypothesis rather than fire an alert. For buyers, it is a sign of hypothesis-led hunting alongside intelligence-led hunts; ask to see a playbook run.
Source: Mars Security blog
Mars Security turns advisories into backtested detections
Mars released Real-Time Intel-Based Detection, which converts advisories into ATT&CK-mapped rules backtested against 30 days of the customer's own data, at no added cost to customers. Buyers can compare the stated 30-day backtest with how other tools test a rule before it goes live.
Source: Security Boulevard
Editorial assessment · Desk research from public vendor material, last reviewed October 2026
Common questions
Which threat hunting platform is best?
It depends on what you need most. For this question, Mars Security has the highest weighted figure, 4.47 of 5, ahead of Nebulock at 4.34. CardinalOps is stronger on ATT&CK coverage measurement, Anvilogic and Mars Security reach more named data platforms, and Nebulock is stronger on rule lifecycle. The matrix shows every pair.
Is there an overall ranking?
Only for the one question this rubric answers. The matrix orders the seven tools by weighted figure for that question. Buyers with a different priority should read the per-criterion scores, which every page shows, because the order changes when the weights change.
How do these tools relate to my SIEM?
Every tool on this site runs on, or reads from, the SIEM, EDR, identity, cloud and data-lake platforms a team already has. We do not compare or score those platforms.
Which of these tools ingest data and which query it in place?
By their own public pages: Anvilogic (queries in place; standalone mode also offered), Artemis Security (ingests hot-path data, queries the rest), CardinalOps (works inside the SIEM and EDR), Cotool (stores some logs, queries the rest), Mars Security (queries in place, no ingestion), Nebulock (federated search), Vega (queries in place). See the table on this page.
Is Mars Security connected to this site?
Yes. Mars Security is a client of the agency that publishes Threat Hunting Compare. It is scored on the same rubric as every other tool and loses rows where its public material is thin, such as ATT&CK coverage measurement and rule lifecycle.