Detect, investigate, and explain threats.
Cases close faster, and your senior people stop burning hours on assembly. Detection, context, investigation, and the final narrative all stand on the same full-fidelity record, so the team spends its time on judgment instead of stitching timelines.
The stack behind the team
Three products, one fabric.
Your team touches three Bloo products, and they never keep a second copy of your data. Each reasons over the same telemetry captured once, inside your cloud.
The substrate. Full-fidelity capture and long-term memory inside your cloud.
Explore Datafabric →Detection over the full record, with research-derived content from Specterforce.
Explore Vantage →Reasoning that reconstructs causal chains and writes the narrative.
Explore SynthAI →Four steps
How an alert becomes an answer.
Step through what happens to a single signal after it fires. Each stage adds what the last one lacked, until your team is holding a narrative it can act on and defend. Follow the signal path through each step.
Vantage
A signal fires on the full record
Vantage detects over full-fidelity telemetry, so the trigger is grounded in everything captured, not a sampled slice.
- Full-fidelity telemetry in view
- Detection content from Specterforce research
- Adversary artifact surfaced in the stream
Datafabric
The alert arrives already explained
Datafabric wraps the signal in the entity histories behind it, so your team opens a case with the context already attached.
- Host, identity, and process histories attached
- Pulled from retained memory, not a lookup window
- No swivel-chair enrichment
SynthAI
The causal chain is reconstructed
SynthAI reasons over the retained history and reconstructs the sequence of events, so analysts review a chain instead of assembling one.
- Causal steps ordered across sources
- Every hop tied back to a record
- The adversary step placed in context
SynthAI
Responders get a narrative they can defend
The outcome is an evidence-backed narrative, every claim citing the record it came from, ready to hand to a responder or an auditor.
- Plain-language incident narrative
- Each statement cites its evidence
- Handed off with the full history behind it
The team's day
What changes for the people on the queue.
The substrate underneath is new. The felt difference is where your team spends its attention, and how far back it is allowed to look.
For your hunters
Hypotheses stop dying at the window edge
Your hunters are no longer capped at 90 days of lookback. A hunt runs as deep as the question, across years of retained telemetry, so a promising thread does not hit a wall where the priced window used to end.
For your analysts
Analysts review the story, they do not build it
SynthAI reconstructs the causal chain from the record, so the person on the queue opens a case that is already assembled. The work shifts from stitching logs together to judging a conclusion.
For your responders
Evidence that survives the case
Nothing ages out mid-investigation. Full-fidelity records stay in reach for the whole life of a case, so the narrative your team hands to leadership or an auditor traces back to the primary record every time.
For your queue
Alerts arrive explained, not raw
A signal reaches the team wrapped in the entity histories behind it. Triage becomes a decision instead of a research project, and the queue moves at the speed of judgment.
Specterforce
Detection engineering as a service.
Most security teams run lean. Nobody has a spare engineer to research campaigns, write detections, and tune out the noise, so coverage decays while the queue grows. Specterforce is the research and detection engineering arm inside Bloo: threat researchers and detection engineers who do that work for you, built around your industry, your infrastructure, and your telemetry.
Research Advisory
Research-driven prioritization: monthly posture reviews, custom threat reports, watchout lists, and a maintained detection backlog.
Best for · Teams with their own detection engineers
Stealthpack
The core service. Specterforce researchers and detection engineers build, publish, and tune customer-specific detections in monthly sprints.
Best for · A detection engineering function without the hiring
Stealthpack Pro
A dedicated pod with a standing operating rhythm: deeper collaboration, faster turnaround, and more frequent tuning.
Best for · An extension of your security engineering team
Live research
The malware families we are tracking.
Specterforce dissects active families, publishes the dossiers, and ships the resulting detections into Vantage. Here are the three latest.
GhostSocks
Advanced SOCKS5 Backconnect Proxy Malware with Residential IP Masking Capabilities
HIGH · Proxy Malware
SmokeLoader Loader
Comprehensive analysis of SmokeLoader malware family, its evolution, and threat landscape
HIGH · Modular Malware Loader
Remcos RAT
Advanced Remote Access Trojan with Persistent Surveillance Capabilities
HIGH · Remote Access Trojan
The full catalog
Every dossier carries the behaviors, the IOCs, and the detections derived from them.
Business outcomes
What the business gets back.
The products matter because of what they return: hours, budget certainty, and risk taken off the table. These are the outcomes your leadership will notice.
01
Senior hours back on real work
SynthAI runs the first pass on every alert and assembles the case, so your most expensive people judge conclusions instead of stitching timelines. The queue moves without growing the team.
Driven by · SynthAI · Datafabric
02
Visibility without a budget trade
Full-fidelity capture with retention economics that scale with time, not volume. Nobody decides which telemetry the business can afford to keep this quarter.
Driven by · Datafabric
03
Faster, defensible closure
Evidence-attached narratives shorten investigations and hold up in front of leadership, regulators, and court. Less time per case, less risk per conclusion.
Driven by · SynthAI · Vantage
04
Coverage without the hiring problem
Research-encoded detections and Specterforce services keep coverage current against live campaigns, without recruiting and retaining a detection engineering bench.
Driven by · Vantage · Specterforce
Feature map
What delivers what.
Each capability on this page comes from a specific product. Follow a row straight to the section that covers it in depth.
| Feature | Delivered by | Read more |
|---|---|---|
Detection over the whole history Detections sweep years of retained telemetry, not a priced window. | Vantage | High-fidelity detections → |
Campaign discovery Alerts assemble into campaigns instead of arriving as a raw queue. | Vantage | Campaign discovery → |
Research-encoded detection content Specterforce research ships as detection content, validated before deploy. | Vantage | Specterforce in Vantage → |
Causal chain reconstruction Investigations return the chain with the evidence attached. | SynthAI | How SynthAI investigates → |
Hot Search across years Query telemetry from years back in seconds, nothing rehydrated. | Datafabric | Hot Search → |
Full-fidelity capture Every field of every event, captured into one substrate. | Datafabric | The pipeline → |
From the blog
What the research desk is writing.
Threat research, detection engineering, and security operations, from the team behind Specterforce.
Crimson RAT: An Analysis of RingBell.exe
In this analysis, we examined a specific sample named RingBell.exe, executed in a controlled virtual environment. The goal is to understand exactly what this malware does from the moment it lands on a
Blog
Fileless Malware and Process-Based Attacks Analysis
Fileless malware is one of the most dangerous and evasive attack techniques. Unlike traditional malware, it leaves no files on disk; instead, it hides inside the system's own trusted processes and too
Blog
EPOINT-AES: Detection Engineering Notes for North Korean APT DLL Loader
Introduction This Detection engineering brief is based on the analysis of an advanced North Korean APT multi-stage malware framework (EPOINT-AES) documented in my previous blog. The malware represents
Blog
EPOINT-AES: North Korean APT Multi-Stage DLL Loader Framework
Introduction This analysis documents a sophisticated multi-stage malware framework discovered during an investigation into North Korean Advanced Persistent Threat (APT) activities. The framework was i
Blog
In depth
Four longer reads for the SOC.
The ideas behind this page, written out in full: the data layer, incident response, and what replaces the priced window.
SOC Modernization and the Data Layer: What Actually Changes
SOC modernization starts in the data layer, how telemetry is retained, structured, and accessible to analysts and agents.
9 min read
AI-Native Incident Response Needs Full-Fidelity History
AI-native IR depends on looking back across years of telemetry in seconds. Learn why sampled storage breaks, and what replaces it.
13 min read
SIEM Alternative: Full-Fidelity Telemetry at Scale
Tired of SIEM ingestion penalties? Bloo retains all your telemetry inside your cloud and scales without punishing visibility.
6 min read
Full-Fidelity Log Retention: What It Means
Full-fidelity log retention means keeping every event, unsampled, in hot searchable storage. Sampling creates blind spots.
6 min read
Go deeper on the capability
Give your team a longer memory.
See what a single alert becomes when detection, context, and reasoning all stand on the same retained telemetry.