I missed this announcement in December, but it carries an important message.
“Gatekeeper Systems, a pioneer in intelligent theft prevention solutions, today announced a significant enhancement to its FaceFirst® platform with the integration of technology from ROC.”
That’s the firm formerly known as Rank One Computing.
The important message is deeper in the press release.
““Facial recognition in retail must be fast, accurate, and accountable,” said Robert Harling, CEO of Gatekeeper Systems. “By embedding ROC’s NIST-verified algorithm directly into FaceFirst, we’re giving retailers a system that performs in real time and stands up to public, operational, and legal scrutiny. It’s AI you can trust—and accuracy you can prove.””
The “accountable” and “prove” part comes from ROC’s demonstrated results in NIST FRTE testing. As well as the fact that people using Gatekeeper Systems now know whose facial recognition algorithm they’re using.
It still shocks me when a company says that they’re using an algorithm, but don’t say whose algorithm they’re using.
Most identity and biometric marketing leaders know that their products should detect attacks, including injection attacks. But do the products detect attacks? And do prospects know that the products detect attacks? (iProov prospects know. Or should know.)
I’ve mentioned injection attack detection a couple of times on the Bredemarket blog, noting its difference from presentation attack detection. While the latter affects what is shown to the biometric reader, the former bypasses the biometric reader entirely.
But I haven’t mentioned how vendors can secure independent confirmation of their injection attack defenses.
“A new European technical standard, CEN/TS 18099:2025, has been published to address the growing concern of biometric data injection attacks. The standard provides a framework for evaluating the effectiveness of identity verification (IDV) vendors in detecting and mitigating these attacks, filling a critical gap left by existing regulations.”
“CEN, the European Committee for Standardization, is an association that brings together the National Standardization Bodies of 34 European countries.
“CEN provides a platform for the development of European Standards and other technical documents in relation to various kinds of products, materials, services and processes.”
And before you say that them furriner Europeans couldn’t possibly understand the nuances of good ol’ Murican injection attacks, look at all the countries that follow biometric interchange guidance from the American National Standards Institute (ANSI) and the National Institute of Standards and Technology (NIST).
So CEN is good.
But let’s get to THIS standard.
More on CEN/TS 18099:2025
The Biometric Data Injection Attack Detection standard can be found at multiple locations, including the aforementioned ANSI. From the current 2025 version:
“This document provides an overview of:
– Definitions of biometric data injection attacks;
– Use cases for injection attacks with biometric data on essential hardware components of biometric systems used for enrollment and verification;
– Tools for injection attacks on systems using one or more biometric modalities.
This document provides guidance for:
– Injection Attack Instrument Detection System (defined in 3.12);
– adequate risk mitigation for injection attack tools;
– Creation of a test plan for the evaluation of an injection attack detection system (defined in 3.9).”
Like (most) good standards, you have to buy it. Current Murican price is $99.
You can see how this parallels the existing standard for presentation attack detection testing.
Which brings us to iProov…and Ingenium
iProov is a company in the United Kingdom. This post does not address whether the United Kingdom is part of Europe; I assigned that thankless task to Bredebot. But iProov does pay attention to European stands, according to this statement:
“[iProov] announced that its Dynamic Liveness technology is the first and only solution to successfully achieve an Ingenium Level 4 evaluation and the CEN/TS 18099 High technical specification for Injection Attack Detection, following an independent evaluation by the ISO/IEC 17025-accredited, Ingenium Biometric Laboratories. Ingenium Level 4 builds on the requirements outlined in CEN/TS 18099, providing an increased level of assurance with an extended period of active testing and inclusion of complex, highly-weighted attack types.”
Ingenium’s injection attack detection testing is arranged in five levels/tiers. The first two correspond to the “substantial” and “high” evaluation levels in CEN/TS 18099:2025. The final three levels exceed the standard.
Level 4:
“Level 4: A 40-day FTE evaluation that further exceeds the CEN TS 18099:2025 standard. Level 4 maintains a high attack weighting while specifically targeting the IAI detection capabilities of your system. Although not a formal PAD (Presentation Attack Detection) assessment, this level offers valuable insights into your system’s PAD subsystem resilience.”
Because while they are technically different, injection attack detection and presentation attack detection are intertwined.
Does your product detect attacks?
And if you adopt a customer focus, the customer doesn’t really care about the TYPE of attack. The customer ONLY cares about the attack itself, and whether or not the vendor detected and prevented it.
Identity/biometric marketing leaders, does your product offer independent confirmation of its attack detection capabilities? If not, do you publicize your own self-assertion of detection?
Because if you DON’T explicitly address attack detection, your prospects are forced to assume that you can’t detect attacks at all. And your prospects will avoid you as dangerous and gravitate to vendors who DO assert attack detection in some way.
And you will lose money.
Regardless of whether you are in the United States, United Kingdom, or the European continent…losing money is not good.
So don’t lose money. Tell your prospects about your attack detection. Or have Bredemarket help you tell them. Talk to me.
Biometric product marketing expert. This is NOT in the United Kingdom.
As I write this, contactless fingerprint scanners cannot submit their prints to the U.S. Federal Bureau of Investigation’s (FBI) Next Generation Identification (NGI) system.
But the FBI does certify such scanners under a special category.
“Hungarian border police are exploring the use of contactless biometric technology made by German startup IDloop in border control and law enforcement….
“The product [CFS flats] was first introduced in 2024 and is the world’s first 3D contactless fingerprint scanner certified by the FBI, according to the firm.”
Note the last four words.
Biometric Update reports news as reported, and I don’t think it’s Biometric Update’s purpose to poke holes in vendor claims. So they just says that THE FIRM SAYS it’s certified, and it’s the first.
Well, IDloop is half right.
Is IDloop’s CFS flats FBI certified?
The way to check certification is to go to the Certified Products List web page at the FBI Biometric Specifications website. You can go there yourself: https://fbibiospecs.fbi.gov/certifications-1/cpl
And if you do, scroll down to the “Firm” area and look for IDloop in the list of firms.
Yes, it’s there, and it has a certification under the Personal Identity Verification (PIV) specification, originally dated 10/30/2024, modified 1/28/2026.
From the CPL.
Here’s the description:
“CFS flats contactless, up to 4-finger, capture device at 500 ppi (PIV-071006) (original 10/24; algorithm update 1/26) Note: Device images a 3-dimensional object, but testing was primarily 2-dimensional – Not for use with CJIS systems.”
Again, the FBI isn’t allowing contactless submissions to CJIS systems such as NGI, in part because the Appendix F specifications assume analysis of fingerprint images on a 2-dimensional object. Obviously very, very difficult with contactless devices that capture 3-dimensional objects.
“Introducing CFS flats—the world’s first FBI-certified 3D contactless fingerprint scanner.“
Um…perhaps I should share a bit of my personal history, for those who don’t know.
From 2009 to 2017 I worked for a company called MorphoTrak. Know where this is going?
But I’m not going to focus on my former employer.
Initial CPL search
Remember that unusual sentence that appears in IDloop’s description of its PIV certification?
“Device images a 3-dimensional object, but testing was primarily 2-dimensional”
I assert that if we can find ANY contactless product in the Certified Products List that uses that same language and was certified before 10/30/2024, then IDloop’s claim of being first is…somewhat inaccurate.
So I checked.
From the CPL.
Two products received PIV certification before October 2024, MorphoWave XP (July 2020) and MorphoWave TP (May 2024). The first was originally certified over 4 years BEFORE the IDloop product.
“MorphoWave XP (formerly MorphoWave Compact) contactless, up to 4-finger, livescan device at 500 ppi (PIV-071006) (alternate enrollment processing 6/23; name change 2/22; contrast stretch 9/21; original 7/20) Note: Device images a 3-dimensional object, but testing was primarily 2-dimensional – Not for use with CJIS systems.”
Subsequent CPL search
And what if you search for the word “contactless” instead and just look at the 4-finger PIV certifications?
If you do so, you can find certifications from 2019 and earlier for products from Advanced Optical Systems (October 2015 May 2017), Safran Morpho (November 2015, under the original name “Finger On The Fly”), and Thales (May 2019). All years BEFORE the IDloop product.
IDloop, meet Advanced Optical Systems
While Advanced Optical Systems is no more, let’s look at the description for that original AOS product.
“ANDI OTG
contactless, up to 4-finger, livescan capture system at 500ppi (PIV-071006). Note: Device images a 3-dimensional object, but testing was only 2-dimensional – Not for use with CJIS systems”
“Huntsville, AL, November 30, 2015 (Newswire.com) –Advanced Optical Systems, Inc made the historic announcement today that their revolutionary, zero-contact “On The Go” fingerprint technology, ANDI® OTG, is the first non-contact fingerprint system to be certified by the US Federal Bureau of Investigation (FBI). The FBI added the device to the agency’s Certified Product List (CPL) on November 27th, 2015.”
When the United States was attacked on September 11, 2001—an attack that caused NATO to invoke Article 5, but I digress—Congress and the President decided that the proper response was to reorganize the government and place homeland security efforts under a single Cabinet secretary. While we may question the practical wisdom of that move, the intent was to ensure that the U.S. Government mounted a coordinated response to that specific threat.
Today Americans face the threat of fraud. Granted it isn’t as showy as burning buildings, but fraud clearly impacts many if not most of us. My financial identity has been compromised multiple times in the last several years, and yours probably has also.
But don’t expect Congress and the President to create a single Department of Anti-Fraud any time soon.
Because this is government-wide and necessarily complex, the bill will be referred to at least THREE House Committees:
“Referred to the Committee on Oversight and Government Reform, and in addition to the Committees on Financial Services, and Energy and Commerce, for a period to be subsequently determined by the Speaker, in each case for consideration of such provisions as fall within the jurisdiction of the committee concerned.”
“9 (9) The National Institute of Standards and 10 Technology (NIST) was directed in the CHIPS and 11 Science Act of 2022 to launch new work to develop 12 a framework of common definitions and voluntary 13 guidance for digital identity management systems, 14 including identity and attribute validation services 15 provided by Federal, State, and local governments, 16 and work is underway at NIST to create this guid 17 ance. However, State and local agencies lack re 18 sources to implement this new guidance, and if this 19 does not change, it will take decades to harden defi 20 ciencies in identity infrastructure.”
Even in the preamble the bill mentions NIST, part of the U.S. Department of Commerce, and the individual states, after mentioning the U.S. Department of the Treasury (FinCEN) earlier in the bill.
But let’s get to the meat of the bill:
“3 SEC. 3. IDENTITY FRAUD PREVENTION INNOVATION 4 GRANTS. 5 (a) IN GENERAL.—The Secretary of the Treasury 6 shall, not later than 1 year after the date of the enactment 7 of this section, establish a grant program to provide iden 8 tity fraud prevention innovation grants to States.”
The specifics:
The states can use the grants to develop mobile driver’s licenses “and other identity credentials.”
They can also use the grants to protect individuals from deepfake attacks.
Another purpose is to develop “interoperable solutions.”
A fourth is to replace vulnerable legacy systems.
The final uses are to make sure the federal government gets its money, because that’s the important thing to Congress.
But there are some limitations in how the funds are spent.
They can’t be used to require mDLs or eliminate physical driver’s licenses.
They can’t be used to “support the issuance of drivers licenses or identity credentials to unauthorized immigrants.” (I could go off on a complete tangent here, but for now I’ll just say that this prevents a STATE from issuing such an identity credential.)
The bill is completely silent on REAL ID, therefore not mandating that everyone HAS to get a REAL ID.
And everything else
So although the bill claims to implement a government-wide solution, the only legislative changes to the federal government involve a single department, Treasury.
But Treasury (FinCEN plus IRS) and the tangentially-mentioned Commerce (NIST) aren’t the only Cabinet departments and independent agencies involved in anti-fraud efforts. Others include:
The Department of Homeland Security, through the Secret Service and every enforcement agency that checks identities at U.S. borders and other locations.
The Federal Trade Commission (FTC).
The Social Security Admistration. Not that SSNs are a national ID…but they de facto are.
And that’s just one example of how anti-fraud efforts are siloed. Much of this is unavoidable in our governmental system (regardless of political parties), in which states and federal government agencies constantly war against each other.
What happens, for example, if the Secret Service decides that the states (funded by Treasury) or the FBI (part of Justice) are impeding its anti-fraud efforts?
Or if someone complains about NIST listing evil Commie Chinese facial recognition algorithms that COULD fight fraud?
Despite what Biometric Update and the Congresspeople say, we do NOT have a government-wide anti-fraud solution.
(And yes, I know that the Capitol is not north of the Washington Monument…yet.)
The U.S. National Institute of Standards and Technology (NIST) says that we should…drumroll…adopt standards.
Which is what you’d expect a standards-based government agency to say.
But since I happen to like NIST, I’ll listen to its argument.
“One way AI can prove its trustworthiness is by demonstrating its correctness. If you’ve ever had a generative AI tool confidently give you the wrong answer to a question, you probably appreciate why this is important. If an AI tool says a patient has cancer, the doctor and patient need to know the odds that the AI is right or wrong.
“Another issue is reliability, particularly of the datasets AI tools rely on for information. Just as a hacker can inject a virus into a computer network, someone could intentionally infect an AI dataset to make it work nefariously.”
So we know the risks, but how do we mitigate them?
“Like all technology, AI comes with risks that should be considered and managed. Learn about how NIST is helping to manage those risks with our AI Risk Management Framework. This free tool is recommended for use by AI users, including doctors and hospitals, to help them reap the benefits of AI while also managing the risks.”
Cybersecurity professionals need to align their efforts with those of the U.S. National Institute of Standards and Technology’s (NIST’s) National Cybersecurity Center of Excellence (NCCoE). Download the NCCoE project portfolio, and plan to attend the February 19 webinar. Details below.
“The NIST National Cybersecurity Center of Excellence (NCCoE) is excited to announce the release of our inaugural Project Portfolio, providing an overview of the NCCoE’s research priorities and active projects.”
“The NCCoE serves as a U.S. cybersecurity innovation hub for the technologies, standards, and architectures for today’s cybersecurity landscape.
“Through our collaborative testbeds and hands-on work with industry, we build and demonstrate practical architectures to address real-world implementation challenges, strengthen emerging standards, and support more secure, interoperable commercial products.
“Our trusted, evidence-based guidelines show how organizations can reduce cybersecurity risks and confidently deploy innovative technologies aligned with secure standards.”
Formal and informal collaborations with other entities.
The NCCoE’s four pillars: Data Protection, Trusted Enterprise, Artificial Intelligence, and Resilient Embedded Systems.
The “forming,” “active,” and “concluding” projects within the pillars, with links to each project.
For example, one of the listed AI projects is the Cyber AI Profile:
“Recent advancements in Artificial Intelligence (AI) technology bring great opportunities to organizations, but also new risks and impacts that need to be managed in the domain of cybersecurity. NIST is evaluating how to use existing frameworks, such as the Cybersecurity Framework (CSF), to assist organizations as they face new or expanded risks.”
This group has published its roadmap, including workshops, working sessions, and document drafts.
And if you are a cybersecurity or identity company needing to communicate how your product protects your users, Bredemarket can help you bring your message to your prospects.
Book a free meeting with me and let’s discuss how we can work together.
Here are details on how Bredemarket works: its services, its process, and its pricing.
“A subject is a human user or NPE, such as a device that issues access requests to perform operations on objects. Subjects are assigned one or more attributes.”
If you have a process to authorize people, but don’t have a process to authorize bots, you have a problem. Matthew Romero, formerly of Veza, has written about the lack of authorization for non-human identities.
“Unlike human users, NHIs operate without direct oversight or interactive authentication. Some run continuously, using static credentials without safeguards like multi-factor authentication (MFA). Because most NHIs are assigned elevated permissions automatically, they’re often more vulnerable than human accounts—and more attractive targets for attackers.
“When organizations fail to monitor or decommission them, however, these identities can linger unnoticed, creating easy entry points for cyber threats.”
Veza recommends that people use a product that monitors authorizations for both human and non-human identities. And by the most amazing coincidence, Veza offers such a product.
People Require Authorization
And of course people require authorization also. They need authorization:
Oh yeah…and to access privileged resources on corporate networks.
It’s not enough to identify or authenticate a person or NPE. Once that is done, you need to confirm that this particular person has the authorization to…launch a nuclear bomb. Or whatever.
Your Customers Require Information on Your Authorization Solution
If your company offers an authorization solution, and you need Bredemarket’s content, proposal, or analysis consulting help, talk to me.
Experienced biometric professionals can’t help but notice that the acronym OFIQ is similar to the acronym NFIQ (used in NFIQ 2), but the latter refers to the NIST FINGERPRINT image quality standard. NFIQ is also open source, with contributions from NIST and the German BSI, among others.
But NFIQ and OFIQ, while analyzing different biometric modalities, serve a similar purpose: to distinguish between good and bad biometric images.
But do these open source algorithms meaningfully measure quality?
The study of OFIQ
Biometric Update alerted readers to the November 2025 study “On the Utility of the Open Source Facial Image Quality Tool for Facial Biometric Recognition in DHS Operations” (PDF).
Note the words “in DHS Operations,” which are crucial.
The DHS doesn’t care about how ALL facial recognition algorithms perform.
The DHS only cares about the facial recognition algorithms that may potentially use.
DHS doesn’t care about algorithms it would never use, such as Chinese or Russian algorithms.
In fact, from the DHS perspective, it probably hopes that the Chinese Cloudwalk algorithm performs very badly. (In NIST tests, it doesn’t.)
So which algorithms did DHS evaluate? We don’t know precisely.
“A total of 16 commercial face recognition systems were used in this evaluation. They are labeled in diagrams as COTS1 through COTS16….Each algorithm in this study was voluntarily submitted to the MdTF as part of on-going biometric performance evaluations by its commercial entity.”
So what did DHS find when it used OFIQ to evaluate images submitted to these 16 algorithms?
“We found that the OFIQ unified quality score provides extremely limited utility in the DHS use cases we investigated. At operationally relevant biometric thresholds, biometric matching performance was high and probe samples that were assessed as having very low quality by OFIQ still successfully matched to references using a variety of face recognition algorithms.”
Or in human words:
Images that yielded a high quality OFIQ score accurately matched faces using the tested algorithms.
Images that yielded a low quality OFIQ score…STILL accurately matched faces using the tested algorithms.
Google Gemini.
So, at least in DHS’ case, it makes no sense to use the OFIQ algorithm.
These results show that identical twins and same-sex fraternal twins give outcomes that are inconsistent with the intended or expected behaviour from a face recognition algorithm.