At Black Hat, each new information supply is a trade-off.
Extra telemetry means higher visibility – but additionally extra information for risk hunters to sift by means of.
From SMA to SAA: Identical Want, Completely different Drawback
Not too long ago, Splunk Assault Analyzer (SAA) outmoded Safe Malware Analytics (SMA) because the official malware risk evaluation platform at Black Hat.
With SMA, we had a easy and efficient sample:
- Submissions exceeding a rating threshold
- Mechanically surfaced to the Risk Hunters’ incident queue on Cisco XDR
It labored nicely. So naturally, we needed the identical final result with SAA.
SAA offers granular information throughout a number of sourcetypes, permitting for vital flexibility in how info is offered. By mapping these information streams collectively, we tailor-made our reporting to ship a complete, cohesive view of our risk panorama.
The Turning Level: Collaboration
That is the place David and Lily stepped in. They constructed a question that:
- Extracts submission metadata (URL, Job ID, engines used)
- Makes use of the Job ID to retrieve high-scoring outcomes (≥85)
- Joins and reshapes each datasets right into a single, usable construction
This was a transformative shift. By tailoring our configuration to satisfy our particular necessities, we unlocked a brand new stage of visibility. This method delivered the deep, actionable insights essential to optimize our workflow.
Constructing the Workflow
With the question prepared, the main target shifted to automation.
As an alternative of ranging from scratch, we reused present ingestion parts and tailored them for this information construction.
Then got here an vital determination: Concentrate on what issues for detection of threats at Black Hat.
SAA can settle for any file format and URLs for evaluation which implies we noticed many protocols getting used, together with:
However solely HTTP had significant quantity and relevance for the occasion.
So, we minimize the remainder. POP3/SMTP would get an opportunity subsequent time round.
This was precision – prioritizing influence over completeness.
Enriching with Community Context and decreasing noise
A file submitted through HTTP doesn’t exist in isolation – it has community context. So, we enriched every submission with:
- Associated visitors telemetry
- Directionality
- Motion context (allowed vs blocked)
This turned remoted outcomes into one thing risk hunters may really examine.
At this stage, we hit acquainted challenges:
- Timestamp normalization (epoch → RFC3339)
- Motion context extraction (allowed vs blocked)
- Site visitors directionality
All mandatory for correct ingestion into XDR.
One concern practically derailed the correlation logic. Site visitors originating from inner zones was routed by means of zScaler, leading to:
- Shared vacation spot IPs
- A number of unrelated occasions bundled collectively
This may create false correlations – precisely the noise we have been making an attempt to keep away from.
The repair? A focused exception to filter it out.
Extremely personalized – however efficient.
The Final result: Higher Indicators for Hunters
The workflow produced a brand new detection stream in Cisco XDR – powered by SAA submissions, enriched with community context.
At first look, some alerts seemed essential based mostly on their attributes of:
- Excessive scores
- A number of inner techniques concerned
- Suspicious JavaScript obfuscation behaviour
However investigation informed a special story.
A reliable Twitter embed. Flagged by heuristics.
False optimistic. And that’s the purpose.
With correct context and evaluation from Assault Storyboard, the crew shortly validated and dismissed it.
And that’s the actual win. This workflow wasn’t about including one other information supply.
It was about:
- Surfacing high-risk submissions routinely
- Offering community context for quicker triage
- Serving to risk hunters dismiss noise quicker
This workflow is way from excellent. It is going to evolve, identical to the whole lot else we construct at Black Hat.
“In the long run, the most effective detection isn’t the highest scored one – it’s the one you’ll be able to act on.”
Take a look at the opposite blogs from our crew at Black Hat Asia 2026.
About Black Hat
Black Hat is the cybersecurity trade’s most established and in-depth safety occasion collection. Based in 1997, these annual, multi-day occasions present attendees with the most recent in cybersecurity analysis, improvement, and developments. Pushed by the wants of the neighborhood, Black Hat occasions showcase content material instantly from the neighborhood by means of Briefings displays, Trainings programs, Summits, and extra. Because the occasion collection the place all profession ranges and educational disciplines convene to collaborate, community, and focus on the cybersecurity matters that matter most to them, attendees can discover Black Hat occasions in the US, Canada, Europe, Center East and Africa, and Asia. For extra info, please go to www.Black Hat.com.
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