Reading Time: 8 minutes
Category: Post-Quantum Cryptography
Author: Derk Bell
The Trusted Signature
You’re alone in a quiet gallery of the Rijksmuseum, the soft hum of security systems barely audible beneath the air conditioning. A dim spotlight falls on a delicate sketch, its ink lines sharp against aged parchment. The plaque reads: Rembrandt van Rijn, ca. 1640. Experts have certified it. It’s catalogued, insured, cited. This is history—undeniable.
Then imagine a whisper from a white-lab-coat technician in the museum’s underground lab: “The ink contains a synthetic dye invented in 1923.” Suddenly, that quiet reverence becomes a conspiracy. The signature? A fake. The sketch? A clever forgery. Somewhere along the line, someone slipped a lie behind the glass. Now: valuations crumble, lawsuits flare, institutions brace for scandal.
The damage isn’t about pigment. It’s about the entire web of belief built around that sketch—the scholars who cited it, the collectors who insured it, the exhibitions built on its story. The forgery doesn’t just challenge the object—it rewrites the narrative we’ve accepted as truth. It rattles our sense of certainty.
In the digital world, we face similar betrayals. But instead of ink and canvas, our trust is built on cryptographic signatures—chains of math and code we rarely question. And like that sketch, they too can be perfect forgeries.
Forged Certs, Broken Chains
In 2012, a team of researchers demonstrated a practical method for exploiting a known vulnerability in the MD5 hash function: collision attacks. Imagine a counterfeiter who discovers that two completely different banknotes—one real, one fake—pass the same machine check because they share an identical serial number. Not because the notes look the same, but because the validation process only checks that number. That’s a collision attack. The attacker creates a harmless-looking certificate that generates a specific digital fingerprint, then crafts a malicious one with the same fingerprint. To the system, they’re indistinguishable. The forgery is perfect—not by mimicking the content, but by mimicking the digital fingerprint.
A group of hackers used this technique to craft a rogue Certificate Authority (CA) certificate—one that browsers and systems would trust as if it were issued by a legitimate root. With it, they could generate valid TLS certificates for any domain: Google, Facebook, your bank, your email provider. Imagine visiting your online banking portal—everything looks normal, the green padlock is there, the URL matches—but behind the scenes, you’re connected to a malicious server controlled by the attacker. Every login, every transaction, every piece of sensitive data flows straight to them. This wasn’t theory. It worked. The infrastructure meant to guarantee authenticity was silently subverted.
Meanwhile, RC4—an algorithm that once powered the encryption behind HTTPS, WEP, and parts of TLS—was leaking secrets like a kid whispering in a made-up language, thinking no one else could understand. To anyone listening closely—and with the right tools—the patterns were obvious. What was meant to be private came out scrambled but guessable. Over time, researchers discovered consistent biases in the way RC4 produced its stream of encrypted bits. With enough captured traffic, attackers could start piecing together session cookies, encryption keys, and other sensitive data. It wasn’t noise—it was a predictable, leaky cipher hiding in plain sight.
These weren’t academic hypotheticals. They were exploited in real-world attacks. In the Netherlands, Diginotar—an official Dutch certificate authority—was compromised in 2011. Dozens of fraudulent certificates were issued, including one for Google, which was used in large-scale surveillance. The breach undermined the Dutch government’s digital infrastructure and led to Diginotar’s collapse. It showed that when a trust anchor falls, everything above it crashes down. Systems gave users the illusion of security—a green padlock, a trusted chain—while adversaries read traffic in cleartext or silently impersonated trusted sites.
The lesson is surgical in its precision: cryptographic systems can appear intact while being fundamentally compromised. The tools of trust—signatures, certificates, encryption—remain cosmetically functional even as their foundations erode. And by the time most people notice, the damage has already been done.
The Real Threat: Inertia
Knowing something is broken is not the same as fixing it.
Take the chips inside your bank card. These contain hardcoded cryptographic algorithms—burned into silicon, certified, and deployed across millions of cards and payment terminals. They’re not built to be updated. If an algorithm in one of these chips is compromised, there’s no way to patch it remotely. The only fix? Replace every card. Every payment terminal. Every piece of hardware that depends on it.
And even if replacement were fast and easy—it isn’t—there’s another hurdle: compliance. Systems like government-issued passports aren’t just technical devices; they’re legal artifacts. Updating them means navigating complex webs of international standards, certification processes, and political agreements. You can’t just flash new firmware to a biometric passport overnight. Every change touches regulations, privacy laws, and cross-border interoperability.
Inertia, then, isn’t just a question of scale. It’s embedded in policy, paperwork, and politics. And it’s why broken crypto often stays broken—long after we know better.
Legacy systems are often built around hardcoded cryptographic algorithms—fixed primitives baked deep into firmware or protocols. They can’t be swapped or reconfigured without rewriting the software, or worse, replacing the entire device. That’s not just an engineering challenge—it’s an economic one.
Now consider the scale: millions of IoT devices, embedded systems, and industrial controllers all running the same vulnerable algorithms. Patching them all—assuming a patch is even possible—is a herculean effort. Many of these devices weren’t built with updates in mind.
And then there’s the bureaucracy. Some standards linger long past their expiration date, not because we don’t know better, but because changing them breaks compatibility or incurs regulatory consequences. The political overhead of replacing a cryptographic primitive in a national ID system can stall updates for years.
Like trying to replace every Enigma machine during a war, switching out broken crypto at scale is slow, dangerous, and often too late.
And yet, the consequences of delay are enormous. Our infrastructure rests on a brittle foundation of trusted but unpatchable code. When it cracks, we can’t just hit “update.” We rebuild—with all the cost, risk, and chaos that entails.
Crypto Agility: Planning for the Next Break
Cryptographic agility means designing systems that are ready to adapt. It’s the ability to swap cryptographic algorithms without overhauling the entire system. You don’t hardcode SHA-256—you make it configurable. You don’t assume a single algorithm will last forever—you plan for the day it won’t.
It’s a mindset. A design philosophy. You expect things to break and make sure your system doesn’t go down with them when they do.
We’ve seen what happens when cryptographic primitives are treated as permanent. One broken algorithm can ripple through industries. Agility contains that blast radius.
This becomes even more urgent in the face of post-quantum cryptography. Some of the most promising candidates have already been broken during NIST’s evaluation rounds [6]. If we’re not ready to pivot, one bad surprise could render entire infrastructures obsolete overnight.
We won’t go into the mechanics here—we’ll save that for another article—but think negotiation, layering, fallback mechanisms. Hybrid approaches that combine classical and post-quantum methods are already gaining traction. They don’t solve everything, but they buy time.
Agility is less about predicting the future, and more about accepting we’ll be wrong—and building anyway.
Conclusion: Trust is a Process
The forged sketch reminds us: trust is fragile. Whether behind glass in a museum or behind the green padlock in your browser, trust is built on signs we’ve learned to believe in—signatures, seals, algorithms.
But when those signs are compromised, the betrayal feels deeper than the failure itself. We don’t just lose security—we lose the story we built around it.
That’s why cryptographic trust must be treated as a process, not a state. It isn’t static, and it’s never final. Every broken algorithm was once considered secure. Every breach started as an assumption that held—until it didn’t.
So we build systems that expect decay. We bake in flexibility. We embrace Zero Trust—not just as a security model, but as a design principle. We don’t blindly trust algorithms, components, or past validations. We verify continuously, assume compromise, and ensure no single cryptographic choice becomes a single point of failure. Zero trust in this context means refusing to believe any algorithm is eternal—it’s about creating systems that question everything, and fail gracefully when something breaks. We replace ink with insight, and permanence with preparedness. Because in the end, trust isn’t proven once—it’s earned again and again, every time we choose to question it.
