From Honeypots to Active Directory Tripwires

THE EVOLUTION OF DECEPTION IN CYBERSECURITY

Cybersecurity Has Always Been a Contest of Visibility

Defenders install controls and monitoring systems; attackers look for blind spots. For decades, one of the most compelling ideas for defenders was simple: create a trap. If an attacker interacts with something that no legitimate user ever should, you know immediately that something is wrong. This is the idea behind deception in cybersecurity.

It started with honeypots—full systems set up as decoys. Later, the concept was refined into honey tokens—small pieces of fake data designed to trip alarms if touched. Each step brought promise but also new limitations. Honeypots were too heavy and costly; honey tokens too uncertain and difficult to operationalize.

Today, the same idea has reemerged in a far more practical form. NodeZero Tripwires™ and the introduction of Active Directory (AD) Tripwires apply the lessons of the past, solve the limitations of early deception technology, and deliver high-fidelity detection in places where attackers can least afford to be caught. To understand why this matters, it helps to trace the history of deception in security.

The Rise of Honeypots

The idea of luring an attacker into a decoy system is nearly as old as networked computing itself. Honeypots emerged in the 1990s as one of the first practical ways to observe attackers in real time. The concept was popularized by researchers such as Clifford Stoll in The Cuckoo’s Egg (1989), and later formalized through organized efforts such as the Honeynet Project, founded by Lance Spitzner around 1999–2000.

A honeypot was typically a system or network deliberately exposed and designed to look attractive to intruders. Once an attacker engaged, defenders could monitor every move, study tactics, and sometimes even trace the origin of the attack.

For researchers, honeypots were invaluable. They provided forensic insight and a window into adversary behavior that no log analysis or intrusion detection system could provide at the time. They helped build early knowledge about malware, worms, and attacker tradecraft.

But honeypots had serious drawbacks:

High Cost and Complexity
Running a convincing honeypot meant standing up and maintaining full operating systems and networks.

Scalability Issues
One or two honeypots could be managed, but deploying them widely across an enterprise was unrealistic.

Limited Detection Coverage
Honeypots were usually isolated. If attackers did not interact with them, they provided no visibility at all.

Risk of Misuse
Poorly configured honeypots could be hijacked and used to launch further attacks.

Honeypots proved that deception was useful — but they were too heavy to become a standard enterprise defense.

Honeypot Lessons

• Valuable for research, not scalable for enterprise defense
• High maintenance costs, limited adoption
• Insightful but reactive, offering little proactive protection

From Honeypots to Honey Tokens

In the early 2000s, researchers began asking: what if the bait didn’t need to be a whole system? What if it could be a single piece of data?

This led to the development of honey tokens, a term widely credited to Lance Spitzner of the Honeynet Project around 2003. A honey token could be a fake username and password, a dummy credit card number, a phony spreadsheet, or even an email address. The key idea was simple: the token had no legitimate use. If anyone touched it, it meant something suspicious was happening.

The Drawbacks of Honey Tokens

As honey tokens moved from concept to practice, their weaknesses also became clear. For all their simplicity, they often failed to deliver consistent, actionable results.

Placement Uncertainty	The first problem was where to put them. If a token was placed in a directory no attacker ever reached, it was useless. If tokens were scattered too widely, they generated clutter or became obvious to an intruder. Security teams were left guessing about coverage, with no guarantee attackers would ever trip one.
False Positives	Honey tokens were designed to never be touched by legitimate users, but in practice, that wasn’t always true. IT staff sometimes stumbled across them during maintenance. Automated scripts or vulnerability scanners occasionally triggered them. Even backup systems or indexing tools could interact with tokens, generating noise.
False Negatives	Even worse, attackers often bypassed tokens altogether. A skilled adversary might target a very specific set of assets or credentials, never touching the decoys. When that happened, defenders were lulled into a false sense of security—assuming no alerts meant no threat.
Operational Overhead	Tokens had to be seeded, rotated, and monitored. At a small scale, this was easy. At enterprise scale, it became a challenge. Without automation, tokens went stale, or their alerts became disconnected from other parts of the security stack.
Integration Gaps	Honey tokens rarely integrated smoothly with SIEM, SOAR, or SOC workflows. An alert would fire, but it was often just a binary signal with no context. Analysts had to dig for details—who triggered it, how, and why. Without that context, honey tokens created more work rather than less.
Perception of Gimmickry	Finally, honey tokens were sometimes dismissed as clever tricks rather than serious tools. Because they often sat on the edges of security programs, they weren’t prioritized or resourced.

For many organizations, they remained proof-of-concept experiments rather than core defenses.

Taken together, these drawbacks meant honey tokens delivered high signal in theory but
unreliable value in practice.

Honey Token Shortcomings

• Guesswork on placement created blind spots
• Alerts were often noisy or absent
• Poor SOC/SIEM integration
• Viewed as experimental, not essential

A New Approach to Deception

The shortcomings of honeypots and honey tokens didn’t mean the idea of deception was wrong.
It meant the execution was incomplete. What was missing was intelligence about where to place
the decoys, how to tune them to attacker behavior, and how to integrate them into real defensive
workflows.

Imagine if deception wasn’t based on guesswork but on live knowledge of how attackers actually
move through your environment. Imagine if decoys were placed precisely where attackers were
likely to look next, not scattered randomly. Imagine if each alert came with full context, like what
was touched, how it was placed, and what attack path it represented.

That is the shift that turns deception from a cool technology into a reliable detection strategy.

NodeZero Tripwires™

The NodeZero® Offensive Security Platform applies this new approach. NodeZero doesn’t simulate
attacks; it performs them safely inside customer environments. In doing so, it reveals how real
attackers can gain access, move laterally, and escalate privileges.

NodeZero Tripwires extend these offensive insights into defensive detection. When NodeZero
identifies a successful attack path, it can automatically deploy a decoy—a Tripwire—along that
path. These may be fake credentials, secrets, or sensitive-looking files placed exactly where an
intruder is most likely to explore next.

The difference from early honey tokens is clear:

• Intelligent placement. Tripwires are dropped on exploited hosts and vulnerable systems, not
  scattered at random.
• Context-rich alerts. Each alert shows where the Tripwire was placed, which weakness it
  defended, and what test led to its creation.
• SOC integration. Tripwire alerts can feed directly into SIEMs, giving analysts the context they
  need for immediate response.
• Customizable deployment. Security teams also have the flexibility to deploy tripwires to
  additional critical and/or NodeZero-recommended systems & data stores.

NodeZero Active Directory (AD) Tripwires

Why Traditional Monitoring Fails

AD is inherently difficult to defend. Its default settings are permissive, its trust relationships complex, and its support for legacy protocols creates exploitable vectors[3].

Common attack techniques such as kerberoasting, AS-REP roasting, and metadata scraping generate logs
that often appear indistinguishable from normal user behavior. SIEM, EDR, and ITDR tools rely on correlation rules and thresholds, which bury subtle identity attacks in the noise of daily operations[3].

SOC analysts, already overwhelmed, rarely detect these attacks until it is too late. By the time a breach has been detected, adversaries may already have domain admin rights, access to sensitive data, and established persistence for weeks or even months[3].

1. Semperis / Enterprise Management Associates (EMA). Rise of Active Directory Exploits: Is It Time to Sound the Alarm?
   2023–2024 survey report. semperis.com
2. Sophos. It takes two: The 2025 Sophos Active Adversary Report. New Sophos X-Ops Research on What Happens After
   Attackers Breach a Company. 2025. news.sophos.com
3. Australian Signals Directorate (ASD), Australian Cyber Security Centre (ACSC), et al. Detecting and Mitigating Active
   Directory Compromises. September 26, 2024. cyber.gov.au

How AD Tripwires Work

AD Tripwires are real accounts created directly inside Active Directory. They are designed to look
exactly like production accounts, blending seamlessly into the environment, but they are never
used in business operations. That makes them irresistible to attackers scanning AD for escalation
opportunities, but any interaction with them is suspicious by definition.

The accounts are tuned to mimic common AD weaknesses and detect specific attack techniques:

Kerberoasting
In a Kerberoasting attack, adversaries request service tickets for service accounts. They then attempt to crack the ticket offline to recover plaintext credentials. An AD Tripwire configured for kerberoasting will trigger as soon as an attacker requests a ticket, producing a high-fidelity alert.

AS-REP Roasting
Attackers exploit accounts that have “Do not require Kerberos pre-authentication” enabled. They request authentication responses and crack them offline. An AS-REP Roast AD Tripwire created without pre-authentication will trigger immediately when such a request occurs.

Metadata Scraping
Attackers often scrape AD attributes such as the “description” field in search of embedded credentials or hints. The Exposed Credential AD Tripwires are seeded with fake password strings. If an attacker attempts to use that password, the Tripwire triggers and exposes the intrusion.

By targeting techniques attackers cannot resist, AD Tripwires deliver early, reliable signals.

Operational Model and Deployment

Deploying AD Tripwires is designed to be straightforward and secure. For each domain, up to three
Tripwire accounts can be created, one for each of the described attack types. A single lightweight
AD Agent runs on the selected NodeZero host. This agent has read-only permissions to the
relevant subdirectory in SYSVOL and checks in at regular intervals, transmitting log data back to
NodeZero for immediate alerting.

Several key design decisions ensure ease of use and security:

Importantly, AD Tripwires can also be validated through built-in end-to-end testing. Security
teams can simulate an attack, see the Tripwire trigger, review the Windows logs generated, and
practice their response. These tests not only confirm that the system works as expected but also
train SOC analysts to recognize and react to alerts in production.

Strategic Fit

AD Tripwires embody the vision behind NodeZero Tripwires: use offense to inform defense. Traditional
detection tools focus on probability. They generate alerts based on unusual patterns or correlation
rules, which requires constant fine-tuning and still produces noise. AD Tripwires uses knowledge of
attacker behavior against attackers, presenting as irresistible lures to generate real signal.

This distinction is powerful. Instead of sifting through false positives, SOC analysts receive a
high-fidelity signal with full context: which identity was touched, how it was attacked, and what
the adversary likely was attempting. That context enables faster, more confident response and
significantly reduces attacker dwell time.

The messaging is clear: proof of attack, not probability.

Personas and Use Cases

Different organizations gain value from AD Tripwires in different ways:

Enterprises often have mature SOCs with SIEM, EDR, and ITDR investments, but they struggle
with alert overload and lack visibility into AD. AD Tripwires cut through the noise and provide
definitive proof of identity attacks, bridging the gap between red and blue teams.

Mid-market organizations may have only a few analysts, often relying heavily on Microsoft
Defender or Sentinel. For them, AD Tripwires provide enterprise-grade detection capabilities
without the cost and overhead of larger platforms.

SMBs often depend on outsourced detection and response. With AD Tripwires in place, even a
small team gains protection against identity attacks with minimal maintenance.

MSPs and MSSPs benefit by delivering demonstrable protection to customers. AD Tripwires
integrate seamlessly into SOC workflows, offering high-value alerts that reduce churn and
strengthen upsell opportunities. Because they are lightweight and low-noise, they help protect
margins while still improving service quality.

Across all personas, the value is the same: precise signals, early detection, and proof that defenses
are working where it matters most.

Outcomes and Proof

NodeZero has already proven in benchmarks like GOAD that AD can be compromised in minutes.
AD Tripwires flip that advantage. If NodeZero can exploit identity weaknesses, so can real
attackers. By placing tripwires along those same attack paths, defenders gain immediate visibility
into adversary behavior.

When an AD tripwire is triggered, the SOC does not just receive a binary alert. Each notification
includes the targeted account, the attack, and the adversary’s likely intent. This provides analysts
with actionable intelligence in context, enabling faster triage and containment.

The outcome is a measurable reduction in dwell time. What once took weeks to detect can now be
caught within minutes. This shift is not just technical. It validates security investment to boards
and executives. It proves that defenses are not only deployed but working in production against
the threats that matter most.

Why AD Tripwires Matter

• ~90% of enterprises worldwide use AD
• ~50% experienced AD attacks in the past 2 years, and >40% of those attacks were successful.
• Attackers often escalate into AD in as little as 11 hours following initial access.

Conclusion

The history of deception in cybersecurity is a story of promise and frustration. Honeypots showed
defenders they could observe attackers directly, but their cost and complexity kept them niche.
Honey tokens promised lightweight traps, but uncertainty, noise, and integration gaps limited their
effectiveness.

For years, deception was an intriguing concept without a practical path to widespread adoption.
NodeZero Tripwires and Active Directory Tripwires change that. By using offensive security
insights to guide placement, they eliminate guesswork. By focusing on lures designed to catch
true malicious behavior, they eliminate noise. By integrating with SOC workflows, they turn
deception into actionable detection.

The result is a solution that delivers what honeypots and honey tokens could not: practical,
scalable, high-fidelity detection where it matters most.

Deception is no longer a gimmick. It is a core part of modern defense.

Evolution of Deception

• Honeypots: heavy, costly, valuable but niche.
• Honey tokens: lightweight but unreliable.
• NodeZero Tripwires: offense-informed,
  context-rich, SOC-ready.
• AD Tripwires: identity-focused deception, cutting dwell time by surfacing proof of attacker behavior early.