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Available for high-impact engineering problems

Abraham Babalola

Systems & Security Engineer

I break complex systems down to first principles. Most of my work lives at the intersection of data systems, web security research, and building low-latency software that does one thing reliably without bloat.

Systems & Research

Dynamic project cards with interactive architecture and engineering trade-offs.

Quantitative Systems & Risk

EdgeRunner

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Automated market discovery and historical edge-matching pipeline built to enforce mathematical discipline and bankroll protection in fast-moving markets.

Automated pipeline comparing live market odds against historical edge distributions to discard low-conviction plays before execution.

Execution Modes: Offline mock settlement, dry-run validation, and live adapter
Market Discovery
Edge Matcher
Risk Controls
Settlement

Synchronizes cross-league timing and combines candidate tickets across multiple rounds into a master board.

Circuit Breakers: Hard exposure constraints and automated abort triggers halt candidate execution under defined adverse loss conditions to protect capital.

Application Security & Fuzzing

Input Mutator

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Constraint-guided permutation engine producing structured, parser-aware mutations to uncover WAF bypasses and proxy/backend normalization desync.

Instead of blind byte fuzzing that gets rejected at the network edge, it understands grammar and encoding layers to test whitelist boundaries and blacklist evasion.

Testing Intents: Whitelist probing, blacklist evasion, and proxy differential gaps
Target Input
Character Mutation
Representation
Transport Encoding

3-stage composition pipeline exploiting Unicode normalization, overlong UTF-8, radix variation, and delimiter ambiguity.

Deployment: Single fat JAR running as a native Burp Suite tab, a desktop GUI with a live normalization inspector, and a headless CLI pipeable to wordlists.

Market Intelligence & Consensus

Forecast Hub

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Business intelligence pipeline clustering live contracts from Polymarket and Kalshi to isolate capital-backed consensus and expose cross-platform divergence.

Filters out meme-coin speculative noise, normalizes disparate exchange schemas, and aligns identical targets side-by-side to flag real operational risk when market consensus splits.

Persistence: SQLite in WAL mode (sub-millisecond reads, zero-lock concurrency)
HTTP/2 Streams
Noise Filter
Two-Tier Matcher
SQLite WAL Storage

Deterministic event clustering without heavy vector search dependencies. Guardrails prevent parameter mismatches (e.g. 2% vs 3% strikes).

Deliberately Lean: No microservices circus or cloud DBs. Concurrent HTTP/2 reads coupled with local SQLite WAL provided instant queries without network overhead.

Edge Runtimes & Distributed State

Cloudflare Edge AI Twin

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Stateful conversational twin service deployed on Cloudflare Workers using Durable Objects over WebSockets with an automatic multi-model failover chain.

Powers the live interactive widget on this site. Manages session lifecycles, per-IP rate limiting, and privacy-preserving audit logs via salted SHA-256 IP hashing on D1.

Latency Impact: -200ms TTFT reduction & zero factual hallucinations

The RAG Decision: Prototype ran classic Vectorize embeddings + top-k retrieval. Cosine similarity over 3 chunks missed basic facts and burned 2x inference quota. Replaced with distilled in-memory context: 100% accuracy, half the neuron burn.

Resilience: Automatically cascades across 4 models (Llama 3.1 8B → Llama 3.1 8B Fast → Llama 3.2 3B → Mistral 7B) to guarantee uptime during upstream provider rate limits.

Data Analysis & Econometrics

Zara Product Economics

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Empirical analysis across 20,000+ fashion SKUs to isolate genuine sales drivers, price elasticity, and wasted clearance markdown budgets.

Rigorous exploratory data analysis quantifying the real ROI of promotional tags, seasonal indicators, and catalog positioning on sales velocity.

Quantified Lift: +62% promotion lift & +14.5% seasonal indicator

Promotion vs. Seasonality: Identified promotions as the single highest revenue driver (+62% sales lift), with seasonal flags contributing +14.5% uplift across winning product segments.

Markdown Leakage: Deep price cuts on unpromoted clearance inventory failed to lift sales volume proportionally, exposing inefficiencies in catalog placement and markdown strategy.

Engineering Focus

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Systems & Edge Runtimes

Building lean, low-latency applications that minimize unnecessary network hops. Stateful WebSockets, Durable Objects, lock-free SQLite WAL storage, and clean architectural boundaries.

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Vulnerability Discovery

Specialized focus on web application business logic flaws, parser normalization discrepancies, and state machine violations where automated scanners fail.

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Empirical Data Systems

Separating actual signal from noise in chaotic distributions. Event clustering, predictive market microstructure, risk constraints, and statistical retail analysis.

AppSec Practice

Security Research & Business Logic Flaws

Most severe modern web vulnerabilities aren't syntax typosβ€”they are business logic flaws: assumptions about user sequence, state validation lapses, and discrepancies between what a reverse proxy accepts versus what a backend parser processes.

I conduct independent research under responsible disclosure programs, designing custom tooling like Input Mutator to test normalization boundaries.

Responsible Disclosure
Parser Desync
State Machine Flaws

Let's talk engineering.

Open to discussions around systems engineering, application security, and high-signal data problems.

Ask me about projects & architecture ✨