REST API Automation

Level: 7 - Integration and Automation Prerequisites: 66_daxc_snapshots.md What You Will Learn: How to use the Rerius REST API server to integrate binary analysis into scripts, pipelines, and external tools.

Starting the Server#

node js/server/server.js

By default the server reads config.dax-ng for port and host:

[server]
port  = 7070
host  = 127.0.0.1

Override at runtime:

PORT=9000 node js/server/server.js
HOST=0.0.0.0 PORT=9000 node js/server/server.js

The web UI is available at https://rerius.sbs.

All API Endpoints#

Every endpoint accepts POST with a JSON body and returns JSON. CORS is enabled for all origins.

Quick Examples#

curl#

curl -s -X POST http://localhost:7070/api/info \
  -H "Content-Type: application/json" \
  -d '{"file":"/bin/ls"}' | jq .

curl -s -X POST http://localhost:7070/api/functions \
  -H "Content-Type: application/json" \
  -d '{"file":"/bin/ls"}' | jq '.[0:5]'

curl -s -X POST http://localhost:7070/api/hottest \
  -H "Content-Type: application/json" \
  -d '{"file":"/bin/ls","n":10}' | jq .

Python#

import requests

BASE = "http://localhost:7070"

def api(route, **kwargs):
    r = requests.post(f"{BASE}{route}", json=kwargs, timeout=60)
    r.raise_for_status()
    return r.json()

info = api("/api/info", file="/bin/ls")
print(f"arch={info['arch']}  stripped={info['isStripped']}  funcs={info['nfunctions']}")

fns = api("/api/functions", file="/bin/ls")
for fn in fns[:5]:
    print(f"  0x{fn['start']:016x}  {fn['name']}")

insns = api("/api/disasm/json", file="/bin/ls", section=".text", limit=20)
for i in insns:
    print(f"  {i['address']}  {i['mnemonic']:<10} {i['operands']}")

JavaScript / Node.js#

const BASE = 'http://localhost:7070';

async function api(route, body) {
    const res = await fetch(BASE + route, {
        method: 'POST',
        headers: { 'Content-Type': 'application/json' },
        body: JSON.stringify(body),
    });
    if (!res.ok) throw new Error(await res.text());
    return res.json();
}

const info = await api('/api/info', { file: '/bin/ls' });
console.log(info.arch, info.nfunctions);

const fns = await api('/api/functions', { file: '/bin/ls' });
fns.slice(0, 5).forEach(fn => console.log(fn.name, fn.start.toString(16)));

The /api/analyze Endpoint#

/api/analyze runs the full analysis pipeline in one call and returns all data:

{
  "info":      { ... },
  "sections":  [ ... ],
  "symbols":   [ ... ],
  "functions": [ ... ],
  "xrefs":     [ ... ],
  "strings":   [ ... ],
  "unicode":   [ ... ],
  "blocks":    [ ... ],
  "hottest":   [ ... ]
}

Use this when you need everything. Use individual endpoints when you need only one thing - they are faster because they skip unneeded analysis steps.

Batch Analysis Script#

import requests
import os
import json
import sys

BASE = "http://localhost:7070"

def scan_binary(path):
    try:
        r = requests.post(f"{BASE}/api/analyze", json={"file": path}, timeout=120)
        if r.status_code != 200:
            return {"file": path, "error": r.json().get("error", "unknown")}
        d = r.json()
        return {
            "file":      path,
            "arch":      d["info"]["arch"],
            "format":    d["info"]["format"],
            "stripped":  d["info"]["isStripped"],
            "pie":       d["info"]["isPie"],
            "functions": len(d["functions"]),
            "symbols":   len(d["symbols"]),
            "strings":   len(d["strings"]),
        }
    except Exception as e:
        return {"file": path, "error": str(e)}

def scan_dir(directory):
    results = []
    for name in sorted(os.listdir(directory)):
        path = os.path.join(directory, name)
        if not os.path.isfile(path):
            continue
        result = scan_binary(path)
        print(json.dumps(result))
        results.append(result)
    return results

scan_dir(sys.argv[1] if len(sys.argv) > 1 else "/usr/bin")

Run it:

node js/server/server.js &
python3 batch_scan.py /usr/bin > results.jsonl

Error Handling#

All endpoints return { "error": "message" } with an appropriate HTTP status code on failure:

• 400 - missing required body field
• 404 - file not found
• 500 - analysis error

r = requests.post(f"{BASE}/api/info", json={"file": "/nonexistent"})
if not r.ok:
    print("Error:", r.json()["error"])

Practice#

1. Start the server: node js/server/server.js
2. Hit /api/info for /bin/ls with curl and inspect the output.
3. Write a script that prints the top 5 hottest functions for every binary in /usr/bin.
4. Use /api/disasm/json to find all call instructions in /bin/ls.

Next#

Continue to 71_building_analysis_scripts.md.