A stolen credential does nothing malformed — Securonix UEBA baselines each user and entity and scores drift from it — the sole way to catch an intruder who logs in legitimately and stays within permissions.
Buy through TechBag
Same software. Better outcome — at a lower cost.
How it’s rated
Full scoreboard ↓Data residency & processing — two different questions
Where data can live
BYO-AWS or BYO-Snowflake
Your own account holds the data lake, in an India region if you choose. ~450 Securonix engineers sit in Bangalore and Pune.
The hard limit
No air gap, ever
The analytics control plane is always Securonix’s cloud. BYO changes where data rests, not who operates the platform.
These are two different obligations and they lead to different vendors. “Data must stay in India” — BYO-Snowflake in an India region can answer that. “Must be air-gapped” — nothing Securonix offers answers it; see LogRhythm SIEM or Elastic Security. Get your compliance team to state which one, in writing, before shortlisting.
Quick answer
This page covers Securonix UEBA — behavioural analytics (UEBA). The other pillars:
Most product pages skip this. We start here — so you buy a capability, not a buzzword.
Analytics that learn how each user and entity normally behaves, then score deviation. It detects attacks that break no rule — an intruder using valid stolen credentials, or an insider misusing access they legitimately hold.
What behavioural baselining catches that a rulebook structurally cannot.
| Dimension | Rules only | Securonix UEBA |
|---|---|---|
| Detection basis | Known-bad patterns written in advance | A learned baseline per user and entity |
| Stolen credentials | A valid login matches nothing | The pattern is wrong, so it scores |
| Thresholds | One global threshold | Peer groups — compared with similar roles |
| Service accounts | Rarely watched | Baselined like people |
| Insider misuse | Permitted actions pass | Unusual access or volume climbs the score |
| Time to value | Day one, for known-bad | 8–16 weeks of baselining first |
| Honest caveat | — | Bounded by your identity data quality |
| Best fit | — | Insider and compromised-account exposure |
UEBA needs clean identity data and weeks of baselining before its scores deserve trust.
Vendors love diagrams; buyers need to know what they’re actually operating. Here’s the whole platform, demystified.
Observes activity per user and entity over time to establish expected patterns: hours, systems, volumes, access paths. The baseline is individual, so an unusual-for-you action registers even when it is common across the organisation. Requires a genuine observation window before it means anything.
Compares each entity against a dynamically constructed peer group rather than a global average. This is what suppresses the false positives that sink naive anomaly detection — routine behaviour for a role stays quiet, the same behaviour from outside that role does not.
Baselines machines, service accounts and applications alongside people. Service accounts matter disproportionately: they hold broad standing privilege, rarely change behaviour legitimately, and their compromise is a common and under-monitored path.
Deviations add to a running risk score per entity instead of firing an alert each time. A slow chain of individually unremarkable actions surfaces as a rising score, which is precisely the pattern rule-based detection misses.
Presents accumulated behaviour as a chronological narrative for the entity, with underlying events attached. Because UEBA and the log data share one platform, the analyst moves from score to raw evidence without leaving the investigation.
A baseline per user and entity, compared against peers — detection for the session where nothing is technically forbidden.
Securonix UEBA learns normal behaviour for each user and entity, compares it against peer groups, and scores the deviation that rules cannot describe. Here is what is inside.
Consumes authentication, directory and access-management data as the behavioural substrate.
Baselines service accounts, machines and applications, not only human users.
Attaches role, department and joiner-mover-leaver status to sharpen what counts as anomalous.
Records which systems and data each entity habitually reaches, and how often.
Learns each entity's own normal rather than applying a shared threshold.
Judges behaviour against dynamically built peer groups to suppress role-normal noise.
Accumulates deviation into a rising score instead of firing on isolated events.
Surfaces misuse by people whose access is entirely legitimate.
Flags valid-credential misuse where no rule is broken and no signature matches.
Detects volume and destination patterns inconsistent with the entity's history.
Assembles scored behaviour into a chronological narrative with evidence attached.
Orders analyst attention by accumulated entity risk rather than alert arrival time.
Behaviour analytics, AI-driven hunting, and the platform it runs on.
Behavioural detection, explained by Securonix.
Where UEBA sits in the platform.
What behavioural analytics surfaces.
Want a live, India-context walkthrough for your environment?
Book a guided demo →Here’s what genuinely sets Securonix UEBA apart — and what it needs from you first.
This is the whole argument, and it is worth stating without hedging. Rule-based detection works by recognising things that are wrong: a signature, a known-bad destination, a malformed request, a policy violation. It is genuinely good at that. But an attacker who has bought or phished working credentials is not doing anything wrong in that sense. They authenticate correctly. They come from an address that looks reasonable. They access systems the account is entitled to access. Every step passes every check, because every step is permitted. There is no rule you can write that catches this without also catching the legitimate user, which is why organisations with excellent rule coverage still get breached through credential theft and still find out months later. Behavioural analytics is the only detection approach that engages with this properly, because it stops asking whether the action is allowed and starts asking whether it is characteristic. The account is entitled to open that share — but this account has never opened it, at this hour, at this volume, in three years of observed history.
Naive anomaly detection fails in a predictable, well-documented way: everything is anomalous to something, so it alerts constantly, analysts stop reading it, and the capability is switched off within two quarters. Peer-group baselining is the mechanism that prevents this, and it deserves more attention than it usually gets in evaluations. Securonix constructs peer groups dynamically and evaluates behaviour against them, not against a global threshold. The effect is to encode organisational reality into the detection logic. When a member of the finance team opens the payroll system, that is unremarkable — their peers do it daily, and scoring it would generate noise forever. When someone from facilities opens the same system, the peer comparison makes it immediately conspicuous even though the raw action is identical. Same event, entirely different meaning, and only peer context distinguishes them. This is also why the quality of your identity and HR data matters so much: peer groups built on a stale directory produce comparisons that mean nothing.
Every other detection approach struggles with insiders for a structural reason: the insider is not evading your controls, they are using them. A departing employee copying a client list has valid credentials, legitimate access to the data, and a business reason to be in the system. Perimeter tooling sees nothing. Signature detection sees nothing. DLP may catch the transfer if the policy happens to cover that route, and frequently it does not. What is visible is the behavioural shift: access frequency rising, breadth expanding beyond the usual working set, volume moving at unusual hours, activity in systems adjacent to but outside the person's actual role. Individually each is explicable. Together, scored over weeks, they form a shape. Combined with joiner-mover-leaver context, the notice period becomes a period of heightened sensitivity rather than a blind spot. Handle this carefully: insider monitoring carries real employee-relations and privacy weight, and deployment should involve HR and legal from the start, not after the first alert.
The 'E' in UEBA is routinely undersold and it may be the most operationally valuable half. Service accounts are the softest target in most estates and the least watched. They hold broad standing privilege because they were provisioned generously years ago. They rarely have an owner who would notice a change. Their credentials sit in configuration files, scripts and CI pipelines, and rotate rarely if ever. And crucially, their legitimate behaviour is extremely consistent — a service account does the same thing on the same schedule, which makes deviation unusually easy to spot. A backup account that suddenly enumerates a directory, an integration account authenticating from a new source, a scheduled job running at an hour it has never run: these are strong signals precisely because the baseline is so tight. If your evaluation focuses only on user monitoring you are examining half the product, and arguably the less differentiated half.
Three limitations, stated plainly. First, Securonix UEBA is delivered within the cloud-native platform and inherits its constraint — there is no air-gapped deployment. If your mandate rules out SaaS entirely, this capability is unavailable regardless of how well it fits, and you should evaluate Exabeam's UEBA, available self-hosted through LogRhythm SIEM. Second, behavioural detection is slow to become trustworthy. Models need eight to sixteen weeks observing normal activity before their output should be acted upon, and early alerts will be noisy. Teams that respond by suppressing aggressively train away the sensitivity they paid for; teams that expect day-one value conclude the product does not work. Neither is a product fault, but both are common. Third, output quality is bounded by identity-data quality. Peer groups built on a stale directory, unowned service accounts and inaccurate role data produce comparisons that mean nothing. If your IAM hygiene is poor, fix that first — UEBA will otherwise amplify the mess rather than reveal it.
Securonix UEBA is for organisations whose realistic threat model centres on credentials and people rather than malware — which, for most Indian enterprises with a meaningful workforce and a modern cloud estate, it does. It is strongest where insider risk is a board-level concern, where privileged and service accounts are numerous, and where a SOC exists to investigate what behavioural scoring surfaces. It is weak value where the security team is too small to act on nuanced signals, where identity data is unreliable, or where you need results this quarter. Against Exabeam — the only true peer, with comparable behavioural heritage — the decision usually turns on two things rather than model quality: Exabeam retains a self-hosted path that Securonix does not, and both meter on GB ingested per day, so price is band against band on your measured volume. Worth actually calculating. TechBag sells both.
Audit directory accuracy, service-account ownership and role data BEFORE deployment. Peer-group quality is bounded by this. Engage HR and legal on insider monitoring scope now — the governance conversation is harder once alerts are firing.
Connect identity, authentication, endpoint and data-access sources. These carry the behavioural signal; volume from elsewhere adds cost without adding baseline quality. Confirm service accounts and machine identities are in scope.
Let models observe. Expect noise and resist over-suppression — this is where value is most commonly destroyed by impatience. Validate peer groups against how the organisation actually works, not the org chart.
Move from alert review to risk-ranked investigation. Establish a documented process for insider cases covering HR and legal involvement before you need it. Re-examine peer groups after every reorganisation.
Modelled on Gartner Peer Insights structure. *Counts and breakdowns are illustrative pending verified review collection.
“It found a compromised service account that had been active for months. Nothing it did broke a rule, which is exactly why nothing had flagged it.”
“Peer grouping is what made this workable. Our previous anomaly tool alerted on everything and we ended up ignoring it entirely.”
“Insider case during a notice period. The behavioural timeline was what made the investigation defensible to HR and legal.”
“Six weeks of noise before the baselines settled. Nobody warned us properly and we nearly abandoned it in month two.”
“Our directory data was worse than we admitted. The peer groups were meaningless until we fixed identity hygiene first.”
“Service account monitoring was the unexpected win. We did not buy it for that and it is where most of our value came from.”
“Strong analytics, but it assumes you have analysts. The scores mean nothing if nobody investigates them.”
“We ran it against Exabeam on the same 90 days of logs. Both are GB-metered, so the decision came down to which timelines our analysts trusted.”
Analyst firms bury this view behind paywalls, and G2 retired its Grid. So here’s TechBag’s synthesis of the SIEM market — tap any vendor to see why it sits where it does.
Execution strength vs product vision — the classic market map, minus the paywall.
Leader six consecutive times — the longest current run.
How much each platform’s behavioural analytics does out of the box vs how freely you can deploy it and control the bill.
Retention and behaviour solved; no air-gap answer.
Positions are TechBag’s illustrative synthesis of public review-platform data and vendor documentation — not a reproduction of any analyst graphic. Verify before relying on it.
Every column has behavioural analytics of some kind; Securonix’s edge is that UEBA is its founding capability rather than an add-on. Where deployment must be self-hosted, the others win.
| Dimension | Securonix | Exabeam | Splunk Enterprise Security | Microsoft Sentinel | Elastic Security |
|---|---|---|---|---|---|
| Position | UEBA-led cloud SIEM on a Snowflake lake | The other UEBA-led vendor | The reference SIEM | SIEM for Microsoft estates | Search-engine-native SIEM |
| Pricing axis | GB/day, tiered bands + commitment | Monitored users + sources | Ingest or workload — historically costly | Per GB ingested per day | Subscription tier + resources |
| Hot retention included | 365 days searchable as standard | By agreement | Priced by volume and term | 90 days, then charged | Yours to configure |
| Behavioural analytics | The founding capability | The founding capability | Available, add-on heritage | UEBA included | Entity risk scoring |
| Self-hosted / air-gapped | None — control plane is always their cloud | LogRhythm SIEM, genuinely on-prem | Cloud, on-prem or hybrid | SaaS only, on Azure | Self-managed, even air-gapped |
| Data custody option | BYO-AWS / BYO-Snowflake — your lake, their analytics | Fully self-hosted available | Fully self-hosted available | Microsoft-operated | Fully self-managed |
| Analyst standing (SIEM MQ 2025) | Leader, six consecutive times | Long-running MQ presence | Leader | Leader | Visionary, not Leader |
| Retrospective hunting | ATS — automatic on new intelligence | Manual hunts | Manual hunts, strong search | Manual hunts | Manual hunts |
| AI in the SOC | Sam — priced on measured analyst work | Nova — seven named agents | Cisco AI Assistant | Security Copilot + MCP | Elastic AI Assistant |
| The thing to plan around | Three CEOs in two years; 120% default overage | Two platforms post-merger | Cisco integration reshaping roadmap | Azure portal retires 31 Mar 2027 | You operate it unless you buy Cloud |
| Best fit | Cloud-accepting estates wanting retention solved | On-prem mandates, or UEBA-led timelines | Engineers who will build with it | Microsoft-standardised estates | Air-gapped, or existing ELK |
Honest fit signals — because the fastest way to lose your trust is to pretend one product wins every scenario.
Securonix UEBA is one of 35 SIEM & log management products TechBag carries. The SIEM & Log Management guide narrows them to a shortlist and shows the reasoning. →
Securonix meters on GB per day, and the lever you actually control is Data Pipeline Manager: one entitlement flexes across three tiers — Analytics at 1.0×, Investigation at 0.5×, Basic at 0.25×. Route firewall noise, verbose DEBUG logging and duplicated sources to the cheaper tiers and your effective capacity rises substantially. Do this classification before you sign, not during onboarding — it is much harder to renegotiate a band downward later. Illustrative rates; Securonix is quote-only.
One warning that matters more than the saving: UEBA can only baseline the behaviour it can see. Filter identity, VPN, endpoint or data-access sources out to control this bill and the peer groups lose exactly the signals that expose a compromised account. Keep identity and access telemetry at the Analytics tier. Illustrative only; Securonix is quote-only.
Securonix UEBA is included in the Unified Defense SIEM entitlement, and Securonix also offers it on top of an existing SIEM you keep — quote-only either way, with no published rate. Inside the platform, the commercial question is the GB/day band rather than a per-user analytics licence. What it costs you elsewhere is preparation: peer-group quality is bounded by your identity data, and the models need eight to sixteen weeks observing normal before their output should be acted on. TechBag quotes in INR with GST.
Included in Unified Defense SIEM
The dependency nobody prices
Plan for this
Whatever the list prices above, TechBag negotiates a significantly better deal — with GST-compliant INR invoicing and local support. Ask us for your discounted quote.
Tell us your requirements and current tools — we’ll model it against what you spend today.
Take this into your next vendor call — including ours.
Is cloud acceptable, given UEBA is delivered within the SaaS platform with no air-gap option?
Is your directory accurate enough that peer groups will mean anything?
Do you have an inventory of service accounts and their owners?
Have HR and legal agreed the scope and handling of insider monitoring?
Who investigates a rising risk score, and within what timeframe?
Has the business accepted 8–16 weeks before output is trusted?
Have you priced Exabeam's GB/day tiers against Securonix's bands on the same measured ingest?
Does your monitoring scope comply with employment contracts and the DPDP Act?
Check your identity data is ready, plan the baselining window, or compare it with Exabeam’s behavioural analytics — in INR/GST.
Stats, ratings, review counts and pricing are illustrative and sourced from public materials; verify before purchase.