Most security teams are not short on alerts. They are short on time to investigate them. A classic SIEM generates signal all day and leaves the hard part — deciding what is real and what to do — entirely to you. 24Observe detects the threat and then investigates it: every detection becomes an incident, and an analyst returns a verdict with the evidence. Detection and investigation, finally in one place.
The dirty secret of the security-information-and-event-management market is that the alert was never the hard part. Finding out whether an alert matters is.
Buy a traditional SIEM and you get a powerful detection engine that will happily produce thousands of alerts a day. What you do not get is anyone to work them. So they queue. Analysts cherry-pick the scary-looking ones, ignore the rest, and quietly tune down anything noisy until the dashboard is calm again — which is exactly how real intrusions slip through a fully-deployed SIEM. The tool did its job. The job it did just was not the one that protects you.
The investigation is where the cost lives. For every alert worth a second look, someone has to pull the related events, line up the timestamps, check the source against threat intelligence, see whether a failed-login burst was followed by a success, figure out which account and which host are involved, and decide if this is an attacker or a misconfigured cron job. That is twenty minutes of skilled work per alert, on a good day, and there are never enough skilled people or enough good days.
24Observe was built around the belief that detection and investigation are one product, not two. The detections are excellent — but their job is to open an incident, and the moment they do, the analyst goes to work: gathering the evidence, tracing the blast radius, and returning a verdict a human can act on or audit. You stop drowning in alerts and start reading conclusions.
There is a quiet second benefit to this design. When investigation is automatic and consistent, the temptation to tune detections down into silence disappears. Teams mute noisy rules because every alert costs them time they do not have; remove that cost and you can afford to keep coverage broad and sensitive. A detection that fires a little too often is no longer a burden to be silenced — it is just a few extra incidents the analyst dispositions in seconds, most of them closed as benign before a human ever looks. Detection coverage and analyst sanity stop being a trade-off, which is the trade-off that quietly hollows out most SIEM deployments within a year of go-live.
A SIEM that hands you ten thousand alerts has not reduced your work — it has relocated it. We do the investigation, not just the detection.
Prebuilt detections are starting points you can trust and then tune — not a marketing number. Each pack groups a real attacker behaviour or operational failure, and most rules map to a recognised attack technique so they slot straight into how your team already thinks.
Brute-force, password spray, account lockouts, multi-factor disabled, new privileged accounts — the front door of almost every breach.
Bulk export, unusually large outbound transfers, database dumps, and data leaving over unexpected channels — the moment information starts walking out the door.
Credentials, keys, and tokens leaking into logs, URLs, or request bodies — the leaks attackers harvest first.
Injection, traversal, and scanning against your applications, surfaced from the events your edge already produces.
Known-bad addresses, anonymising networks, and listed indicators matched the instant an event arrives.
Prompt injection, runaway tool loops, token and cost abuse, sensitive tool use, and tool-protocol manipulation.
Root usage, key creation, audit-trail tampering, and console abuse in your cloud accounts.
New users, privilege escalation, persistence via scheduled tasks and SSH keys, reverse shells, and recon on your hosts.
Memory exhaustion, disk-full, kernel faults, service crash loops, and interface or routing failures across your estate.
Fatal errors and error-rate spikes — the operational signals that sit right next to security ones.
Detections use the same readable query language as your everyday search — no proprietary scripting dialect to certify in. A rule is a query, a window, a threshold, a severity, and an attack-technique tag. When it matches, it opens an incident through the same pipeline and routing as everything else. Authoring a new detection is a one-line change a responder can make between calls, not a project.
Some attacks are invisible in any single event and obvious across several. The platform detects sequences — a wall of failed logins then a success for the same account — and cardinality patterns — one source touching ten distinct accounts, the fingerprint of a spray or enumeration sweep. These higher-order detections open incidents the analyst investigates exactly like the rest.
Every public address in an incoming event is checked against threat intelligence as it lands — known-bad indicators, anonymising and datacenter networks, and listings — and flagged inline. Bring your own private indicators too: addresses, domains, and file fingerprints, scoped to your organisation. A match is both a one-line detection and a powerful corroborating signal the analyst weighs in its verdict.
Source addresses resolve to geography and network owner inline. Your own directory of identities and assets stamps risk and criticality onto matching events. So "a failure on a critical asset, from a high-risk source, outside business hours" becomes a single readable query instead of a join across three different tools.
This is what separates 24Observe from a detection engine with a dashboard. The instant a detection fires, the analyst investigates — and you get a verdict, not a row in a queue.
Abstract claims are easy. Here is the concrete path a single detection travels — the same path every one of them follows, every time, without a human kicking it off.
A burst of failed logins hits one of your services. The access-and-identity pack has a brute-force detection watching exactly this, and the moment the count crosses its window threshold it does what every detection does: it opens an incident. Not a line in a log, not a muted notification — a first-class incident, the same kind a failed health check or a saturated host would open, carrying the rule’s severity and its attack-technique tag.
Because the incident is wired into the live map of your environment as it opens, the affected account, the source address, and the host behind the service are already attached. There is no "now go figure out what this touches" step — the blast radius is part of the incident from the first second. That wiring is also what lets the investigation start instantly instead of from a cold search.
Now the analyst goes to work. It does not take the failed-login spike at face value — a spike alone is often a misconfigured client or a forgotten cron job, not an attack. It corroborates. Was there a successful login for that account immediately after the wall of failures? Is the source address flagged by threat intelligence, or coming from an anonymising network? Is the geography impossible for this user? Has this account touched anything sensitive since? Each question is answered by a read-only tool against your real telemetry, and each answer is recorded as a citation.
The verdict that comes back is a decision, not a description. If the evidence converges — failures, then a success, from a flagged source, in an impossible location — it is a confident true positive, with every supporting record linked so a human can verify the call in seconds rather than reconstruct it over twenty minutes. If the evidence is thin or contradictory, the analyst says so and routes it to a person instead of crying wolf. Either way, the recommended next action — block the source, force a password reset, isolate the host — is proposed for a human to approve, never executed automatically.
Suppose the same intrusion tripped five detections at once across a few services. Rather than paging you five times, the platform recognises that they share a root and collapses them into a single case, so you investigate the incident, not the echoes. And when your analyst reviews the verdict and corrects it — confirms it, downgrades it, adds a note — that correction is captured and feeds future investigations, so the system gets measurably better at reading your environment over time.
Finally, none of this traps you inside 24Observe. The detection fires a signed webhook to your own tooling and SOAR the instant it matches, and a gap-free export streams your audit trail for any downstream system to consume. You can run 24Observe as your detection-and-investigation brain and still feed every other tool you own. The point was never to lock the data in — it was to make sure no detection ever again dies unread in a queue.
Turn on the packs, point your sources at the platform, and watch detections become investigated incidents — with the evidence and the next step already attached.