What we still need to verify : 2 points in this profile are not yet confirmed against vendor documentation.
- Current module naming and packaging within the unified platform: confirm
- Supported inline integration points and connector list: verify against vendor docs
Treat these points as unconfirmed. They are open items in the catalog's verification queue, and this note stays until each is checked against the vendor's documentation.
What it does
Cequence comes at API security from the abuse and bot defense side, which shapes the whole product. Discovery runs in two directions. Externally, it enumerates internet facing API attack surface the way an attacker would, resolving domains and subdomains, fingerprinting hosts and identifying exposed endpoints without any agent inside your network. Internally, it analyzes traffic to build an inventory, infer schemas and flag posture issues: unauthenticated endpoints, sensitive data in responses, specification drift.
The protection layer is where the product is strongest. It analyzes request streams to distinguish automated clients from human driven ones and to recognize distributed, low volume campaigns that never trip a rate limit. The signals combine client fingerprinting, behavioral sequencing across a session, and correlation of activity sharing characteristics across many source addresses. This catches attacks made entirely of technically valid requests: credential stuffing, account takeover, gift card enumeration, scraping, inventory hoarding, fake account creation. Because the behavior is legitimate at the protocol level, signature matching cannot see it. Responses are graduated: block, throttle, deceive with a synthetic response, or log.
Where it fits
This is a runtime control on production traffic. Deployment ranges from passive analysis of mirrored traffic to inline enforcement via load balancers, CDNs, API gateways and container platforms. It is operated by a security team, often alongside fraud and platform engineering, because the attacks it stops are a business problem before they are a security problem. The prerequisite is a clear view of where public API traffic terminates, plus agreement on what to do when the platform decides a client is automated.
Strengths
- Bot and abuse detection is the core competence and is genuinely differentiated, catching attacks made of well formed requests.
- External discovery finds internet facing API surface without deploying anything, useful for inventory and acquisition due diligence.
- Graduated responses let you degrade or deceive rather than only block, slowing attackers without alerting them to the detection.
- Deployment flexibility covers out of band analysis and inline enforcement depending on risk appetite.
Limitations
- Focused on runtime defense rather than pre production testing, so it does not replace an API testing tool in the pipeline.
- Behavioral models need a baseline period, and aggressive policies risk blocking legitimate automation such as partner integrations.
- Inline deployment adds a component to the request path with the availability and latency implications that carries.
- Detection is an arms race, and quality degrades as attacker tooling adapts.
Who it suits
Consumer facing businesses where APIs carry transactional value and automated abuse has a measurable impact: retail, travel, financial services, ticketing. Teams whose main need is finding vulnerabilities in internal APIs before release will get more from a testing focused product.
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