Josuanstya Lovdianchel
Written by

Josuanstya Lovdianchel

Josuanstya Lovdianchel is a Business Operations and Product professional with 4+ years of experience spanning product management, growth strategy, and AI-driven automation. He has shipped products end-to-end at scale — most notably at detikcom, Indonesia's largest digital media platform, where he delivered an ERP contributor platform to 100+ users with 100% adoption within one month of launch and led cross-functional teams across Engineering, AI, and Design. A certified Microsoft Azure practitioner with hands-on Python skills, he brings a data-first approach to every problem — from analyzing 10,000+ user reviews to surface product strategy, to building AI-powered notification systems targeting double-digit CTR uplifts. At Plexicus, he applies the same product and automation mindset to business operations, turning complex workflows into scalable systems.

78% of AI-Generated PRs Contain a Vulnerability. Here's What We're Seeing.
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Across thousands of AI-generated pull requests scanned in the past six months, 78% contained at least one vulnerability that survived the human review pass. The failure modes are not random. They cluster. Here is the data, the incidents, and what your team can do about it.

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Regex SAST gives you thousands of theory-class findings. LLM-assisted review gives you confident rewrites that may not run. Deep Code Analysis is the third layer: a structural model of your code that proves which findings are real, reachable, and worth fixing.

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AI原生修复:应对氛围编码安全挑战
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Vibe Coding 安全:在 AI 生成代码上线前确保其安全
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AI 编码工具正在编写近一半的新代码。其中 45% 的代码在发布时至少包含一个漏洞。Vibe Coding 安全是一种保护由 AI 创建的软件安全的实践——在风险到达生产环境前进行检测、优先级排序和修复。

Josuanstya Lovdianchel Josuanstya Lovdianchel ·
Ready to validate what matters?

Ready to validate what matters?

Plexicus is Proof-Driven AppSec: validated findings, contextual understanding, and reviewed remediation — anchored in evidence, scoped with you.

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SAMPLE HANDOVER · ILLUSTRATIVE

Sample evidence handover

A trimmed view of what your team receives at the end of an AI Swarm Pentest engagement. Real engagements include full technical evidence, executive narrative, and a remediation plan.

VALIDATED FINDING Evidence attached

Server-Side Request Forgery in webhooks/receiver

demo-project/sample-app · src/webhooks/receiver.py:42

SeverityHigh CVSS 3.18.6 Priority79 Confirmedvia replay

Untrusted caller-supplied URLs reach an internal egress without an allowlist. Replayed in a sandbox against a fresh authorised target — the same control was validated to fail twice.

REVIEWER-READY REMEDIATION Merge-ready PR

Validate the target URL against an allowlist of permitted hostnames. Reject private/internal IP ranges. Enforce HTTPS only.

plexicus/remediation/webhooks-ssrf 3 changed · 0 new files
42resp = requests.get(target_url)
42+if not is_allowed_host(target_url):
43+  raise WebhookRejected(target_url)
44+resp = requests.get(target_url, timeout=5)
Every engagement hands over:
  • Executive briefing
  • Validated findings list
  • Merge-ready PRs
  • Compliance mapping (NIS2 · DORA · CRA)