Sign up to save your podcasts
Or
Share Won't Fix Episode 3: With KTLYST Labs' Assaf Kipnis
Share to email
Share to Facebook
Share to X
Share to email
Share to Facebook
Share to X
Or
Won't Fix Episode 3: With KTLYST Labs' Assaf Kipnis
Assaf Kipnis spent years hunting financially motivated bad actors on Meta's e-crime team and in Google's Ads Trust & Safety org.
He now runs KTLYST Labs, where he's building the threat intelligence tooling he always wished existed inside big platforms. We get into the practical realities of scam fighting — what's actually changed in the AI era, what hasn't, and why so much of the industry's effort gets aimed at the wrong targets.
About the guest:
Assaf Kipnis is the founder of KTLYST Labs. Previously: Meta e-crime, Google Ads Trust & Safety, ElevenLabs, LinkedIn threat intel.
What We Cover:
- Why AI isn't reinventing scams — it's just adding a more convincing final layer to playbooks that have existed for years.
- The asymmetry problem: bad actors run conferences, sell each other tools, and share playbooks on Telegram, while defenders can't share findings across teams at the same company.
- A case study in what actually works — how changing product, policy, and operations together pushed a misinformation-for-profit ring off the platform in a week.
- Why "accounts taken down" is a near-useless metric, and the "learned futility" it creates inside big trust & safety orgs.
- The Swiss cheese model of abuse prevention, and why chasing a single silver-bullet solution keeps companies chasing their tail.
- Where regulation has teeth (banking) and where it's mostly performative (social media), plus the cross-platform gap no one is addressing.
- How AI is changing investigative work — compressing a week of open-source research into two hours — and why that makes entry-level talent pipelines a real concern.
Episode Highlights:
00:00 Intro
01:06 Professional Background and Career Journey
03:47 AI's Role in Scaling Rather Than Changing Scams
07:05 Adversary Collaboration vs. Defender Silos
09:02 The Frame Rate Discovery Example
10:26 KTLYST Labs and Operationalizing Threat Intelligence
12:40 AI's Impact on Investigation Work
15:15 Career Entry Points and AI's Impact on Junior Roles
20:38 The NextTag Affiliate Program Attack
23:00 The Misinformation Campaign Investigation
27:52 The Limitations of Location-Based Solutions
30:30 The Futility of Single-Solution Thinking
33:47 The Reality of Platform Defense Goals
34:50 Government Regulation and Enforcement Challenges
40:31 The Problem with Takedown Metrics
Links:
Assaf Kipnis
KTLYST Labs
Rob Leathern
View all episodes
By Rob LeathernAssaf Kipnis spent years hunting financially motivated bad actors on Meta's e-crime team and in Google's Ads Trust & Safety org.
He now runs KTLYST Labs, where he's building the threat intelligence tooling he always wished existed inside big platforms. We get into the practical realities of scam fighting — what's actually changed in the AI era, what hasn't, and why so much of the industry's effort gets aimed at the wrong targets.
About the guest:
Assaf Kipnis is the founder of KTLYST Labs. Previously: Meta e-crime, Google Ads Trust & Safety, ElevenLabs, LinkedIn threat intel.
What We Cover:
- Why AI isn't reinventing scams — it's just adding a more convincing final layer to playbooks that have existed for years.
- The asymmetry problem: bad actors run conferences, sell each other tools, and share playbooks on Telegram, while defenders can't share findings across teams at the same company.
- A case study in what actually works — how changing product, policy, and operations together pushed a misinformation-for-profit ring off the platform in a week.
- Why "accounts taken down" is a near-useless metric, and the "learned futility" it creates inside big trust & safety orgs.
- The Swiss cheese model of abuse prevention, and why chasing a single silver-bullet solution keeps companies chasing their tail.
- Where regulation has teeth (banking) and where it's mostly performative (social media), plus the cross-platform gap no one is addressing.
- How AI is changing investigative work — compressing a week of open-source research into two hours — and why that makes entry-level talent pipelines a real concern.
Episode Highlights:
00:00 Intro
01:06 Professional Background and Career Journey
03:47 AI's Role in Scaling Rather Than Changing Scams
07:05 Adversary Collaboration vs. Defender Silos
09:02 The Frame Rate Discovery Example
10:26 KTLYST Labs and Operationalizing Threat Intelligence
12:40 AI's Impact on Investigation Work
15:15 Career Entry Points and AI's Impact on Junior Roles
20:38 The NextTag Affiliate Program Attack
23:00 The Misinformation Campaign Investigation
27:52 The Limitations of Location-Based Solutions
30:30 The Futility of Single-Solution Thinking
33:47 The Reality of Platform Defense Goals
34:50 Government Regulation and Enforcement Challenges
40:31 The Problem with Takedown Metrics
Links:
Assaf Kipnis
KTLYST Labs
Rob Leathern