Token Observe vs AI security platforms
Use Token Observe to govern the requests you route through its gateway. Broader AI security coverage belongs alongside it; pattern-based detection remains heuristic.
On detection, coverage and the estate that never touches a gateway, they win.
Detection quality is these vendors’ product and it is not Token Observe’s. Palo Alto publishes Prisma AIRS as a runtime firewall with discovery, model scanning, red teaming, MCP inspection and DLP, plus an AI gateway with budget limits, rate limits and rules on what each registered agent may do; Cisco publishes AI Defense as asset and MCP discovery, supply-chain scanning and runtime protection; Noma, Zenity, WitnessAI and Lakera each publish their own on prompt-injection defence and intent-aware enforcement. Every one of those descriptions is the vendor’s, untested here. Against a nine-pattern heuristic, a maintained detection product ought to win, and this product’s documentation concedes it rather than arguing: the residual risk carries a named CISO’s written acceptance.
Coverage is the larger advantage. Token Observe sees what routes through the gateway and nothing else, while a platform on the network path or in the browser sees traffic that never presents a Token Observe credential: most of the shadow AI in a real organisation. Procurement is the third: these vendors can generally hand you a certification and Token Observe cannot, and if that is your gate the comparison ends here in the other product’s favour.
Token Observe and AI security platforms, row by row
Where these two differ, one row at a time.
Detection is the product: trained classifiers, red teaming, supply-chain scanning.
Detection is one policy input among seven trigger kinds, published with its confidence scores so a policy can set its own threshold.
Runtime filtering of the traffic that matched, and in several, published rules on which tools or operations an agent may use.
Deny-by-default action-level permissions, an approval bound to the exact payload, a hard USD ceiling and a kill switch — the damage bounded rather than the string caught.
The whole AI estate, including browsers, unmanaged devices and agents no gateway sees.
Only what presents a credential to the gateway. Everything else is a radar finding, and chasing it is your work. The endpoint seat hook is preview and not production-eligible.
You grant the platform access to inspect.
You configure an outbound feed in a console you already administer, on a credential this deployment issued. No standing broad credential runs the other way; the two shipped pull connectors, GitHub Copilot and Cisco Umbrella, are the named exception and stay off until you supply the key.
Ask each vendor which certifications and test results it holds, for what scope and to what date.
None held. A source-available licence — itself a template pending counsel — a published residual-risk register, and a 30-day evaluation written so your security team may attack it before you buy.
- beat 01Name the caller
- 1Authenticate
- 2Resolve the agent
Nothing is decided for an anonymous caller. The key resolves to one registered agent with a named owner, and its roles, its ceilings and any stop switch in force are read live from the store on every request, not from a cached copy, so a suspension takes effect on the next call instead of after a redeploy.
- beat 02Start the record, then read what is being sent
- 3Open the trace
- 4Sanitise
- 5Scan
The trace is opened before anything can refuse the request, which is why a blocked call is recorded as thoroughly as one that went through. Only then is the text normalised and scanned, in that order, so the detectors see what the model will read rather than what a human reviewer can see.
- beat 03Decide once
- 6Govern
- 6bIntersect with the named human
- 7Enact
One function returns one verdict: allow, block, or hold it for a named person to approve. Every check lives in that one place rather than scattered along the path, which is what makes it possible to read your rules and know what they do.
- beat 04Send it, and only then spend the money
- 8Route
- 9Call upstream
Routing fixes which provider and model will serve the call, so where an agent has a USD ceiling it is tested against the price you will pay, not the one the caller typed. Routing is also the last step that can still refuse locally: after it, the request has left your network.
- beat 05Govern the answer, then count the cost
- 10Govern the response
- 11Meter and record
A tool call the model proposes is judged before it reaches your agent. Metering runs last and on every ending, including the refusals and the streams a client abandoned halfway, because the tokens were spent either way and a partial trace is still evidence.
Step names and their grouping are the product’s own, and the order is encoded in the evaluator rather than drawn for the page.
What the detectors can identify.
Prompt-injection scoring is nine weighted heuristics over sanitised text, scored 1.25 times higher when the text arrived as a tool result, because indirect injection arrives through tool output far more often than through the user turn. It is not a model and it has false negatives. Sensitive-data detection is patterns too: eleven classes, three checksum-validated, confidence published per kind rather than averaged into a marketing number, and free-text personal data not detected at all.
Limit the actions an injection can trigger.
Assume the detection missed it, because sometimes it will. What remains is the deterministic layer, and this is the part Token Observe is arguing for. Permissions are action-level and deny-by-default: an action no role names is refused, an explicit deny beats every allow, and a delegation chain intersects rather than unions. A hijacked agent inherits the authority it already had, and nothing more.
- An approval bound to one payload
- Bound to the SHA-256 of the canonical action plus its execution context, single-use through a compare-and-set, expiring at 60 minutes by default. A retry with one argument changed is a mismatch rather than near enough.
- Ceilings reserved before egress
- Hard USD limits per request, per rolling hour, per UTC day and per UTC month, reserved in one per-agent transaction before the call leaves. A kill switch is checked first in the pipeline.
- What it still cannot refuse
- A proposal it is never shown. Tool calls the model proposes are evaluated on the way back, but an agent that routes none of its traffic through the gateway is caught by the radar, if you have fed it, or not at all.
Which of the two to put in.
Read the left one first. If two of those describe you, buy the other thing. If the right column describes you, the next step is thirty days with the source on your own hardware.
When to choose AI security platforms
- You need coverage of the whole AI estate — browsers, unmanaged devices, SaaS copilots — rather than of the agents that hold a credential you issued.
- Detection quality is the requirement: supply-chain scanning, red teaming, or a maintained injection classifier rather than nine published heuristics.
- Your procurement process requires SOC 2, ISO certification or an independent penetration test from the vendor. Token Observe has none of those.
- You are consolidating security vendors, and a second contract for a control that overlaps at the edges is a harder sell than a wider deployment of one you have.
When to choose Token Observe
- You have one of these platforms already and the gap is the action rather than the content — what the agent was allowed to do, who approved it, whether it happened.
- The refusal has to be deterministic and explainable: a named permission, a named policy, a named approver, not a score you have to defend to an auditor.
- You want your security stack’s verdicts to become policy inputs, with your consoles pushing outwards rather than a new vendor holding a standing key.
- Self-hosted with zero vendor egress is a hard requirement, including air-gapped environments, which the licence is drafted to permit though it remains a template.
If the left-hand column describes you, that is still worth an email: a short reply costs both of us less than an evaluation that ends in the same place.
See the thirty-day evaluationThe 7 named products in this category
This page argues about the category. If you have already shortlisted a product, these go head to head with it.
Keycard
Keycard decides whether an agent gets a credential for this tool call. Token Observe decides on the payload, then has a second tool check what a contracted action did.
Palo Alto Prisma AIRS
Prisma AIRS scans the content and caps what a workspace may spend and call. Token Observe decides whether one named agent may make this exact call, and who approved it.
Cisco AI Defense
AI Defense attaches a policy to an application’s connection and inspects what crosses it, tool calls included. Token Observe attaches permissions to an agent and decides what it may do.
Zenity
Zenity gets into the path the agents are already on. Token Observe is the path the agents are pointed at.
Noma Security
Noma sets which agents, tools and data are approved and enforces that at the control points you already run. Token Observe sits in the request path and decides on the call itself: its arguments, its price and the approval for that exact payload.
Lakera
Lakera tells your application the content is an attack. Token Observe is the thing that refuses to send it.
WitnessAI
WitnessAI stands in front of the interaction and classifies the intent. Token Observe stands in front of the API call and decides the action, its cost and its evidence.
The other comparisons
The other 6 categories, each opening with the case for the alternative.
Is Token Observe an AI firewall?
No, and the roadmap names a generic AI firewall, prompt scanner or red-team platform as one of seven strategic non-goals. The stated consequence is to consume threat and identity signals from those systems rather than lead with a complete AI security platform. Token Observe does inline PII and secret detection and injection heuristics, because a decision point that cannot see the payload cannot decide about it, but those are policy inputs rather than the product.
How do we feed our security tooling into Token Observe?
You configure an outbound feed in a console you already administer, pointing at a receiver on a credential Token Observe issued. Vendor-shaped receivers exist for six: Cloudflare Logpush, Palo Alto Strata Logging Service, Zscaler, Netskope, Elastic and Splunk. Token Observe holds no standing broad credential into your security stack, and the two shipped pull connectors are the named exception: GitHub Copilot seat spend and Cisco Umbrella activity each hold a narrow, read-scoped key you supply into that vendor’s console and can withhold by not setting it. Everything else points inwards, so the worst a compromised deployment can do to your SIEM is stop receiving from it.
Have you tested Prisma AIRS, Cisco AI Defense or Lakera against this?
No. Every strength attributed to those products here is their vendor’s own public material, untested, and there has been no witnessed bake-off. Nor should the absence of a capability from this page be read as its absence from a vendor’s product. What is available instead is a thirty-day evaluation so your security team, or a third party you commission, can read, run and attack the software on your own deployment. Publication rights are narrower than the testing right: benchmark results with no pre-approval provided the version and configuration are named, security findings after coordinated disclosure. All under a licence still pending counsel.
Tell us which way you are leaning, and why.
Create a cloud account and workspace. No card or server installation. Model calls and Google BigQuery scans can incur separate provider charges.