spacebook: original code

aaaa/spacebook/README.md

@@ -19,63 +19,44 @@ We're given a boresight vector $\vec{v}\in\mathbb{R}^3$ for each star, and a mag
 
 ![Distribution of star magnitudes for catalog and unknown sets](spacebook-magnitude-distribution.png)
 
-*Note that code from here on in this report is reconstructed, since I accidentally overwrote the original copy. I took the chance to use scipy for Kabsch this time instead of the original package I used, [`rmsd`](https://github.com/charnley/rmsd).*
-
 My immediate suspicion was that we could take the outliers (simply by thresholding for stars with $m>500$) and, for each, directly match it to the catalog by finding the star with closest magnitude in the catalog:
 
 ```{.python}
-def match_brightest_stars(unknown, catalog):
-    brightest = []
-    catalog_matches = []
-    for star in unknown:
-        if star['m'] < 500:
-            continue
+refstars_magsorted = sorted(refstars, key=lambda x:x['m'])[::-1]
 
-        # find closest magnitude in catalog
-        match = np.argmin(np.abs(np.array([s['m'] for s in catalog]) - star['m']))
-        print(f'[+] matched {star} to {catalog[match]}')
-        brightest.append(star)
-        catalog_matches.append(catalog[match])
+catalog_magnitudes = np.array([x['m'] for x in catalog])
+matches = []
 
-    return brightest, catalog_matches
+for idx, star in enumerate(refstars_magsorted):
+    if star['m'] <= 500:
+        break
+    match = np.argmin(np.abs(catalog_magnitudes-star['m']))
+    matches.append(match)
 ```
 
 We can then align those brightest stars to their closest magnitude matches using the Kabsch algorithm:
 ```{.python}
-def orient(ref, catalog):
-    P = [s['v'] for s in catalog]
-    Q = [s['v'] for s in ref]
-
-    rot, rmsd = Rotation.align_vectors(P, Q)
-    print(f'[+] aligned; rmsd = {rmsd}')
-    return rot
+P = np.vstack([x['v'] for x in [catalog[i] for i in matches]])
+Q = np.vstack([x['v'] for x in refstars_magsorted[:4]])
+print("rmsd: {}".format(calculate_rmsd.kabsch_rmsd(P,Q)))
+rotation_mtx = calculate_rmsd.kabsch(P, Q)
+rotation = Rotation.from_matrix(rotation_mtx)
 ```
 
-Then for each unknown star with vector $\vec{v}$, we can find its catalog index by evaluating
+Knowing the rotation, we can rotate all stars into the catalog reference frame and then evaluate
 $$\arg\min_{\vec{u}\in\text{catalog}} \norm{\vec{u}-\vec{v}}_2$$
-for every challenge:
+for each unknown star with vector $\vec{v}$ to find the closest star in the dictionary:
 ```{.python}
-for _ in range(5):
-    unknown_stars = read_starfile(r.recvuntil('\n\n').decode())
-
-    # find pairs
-    unknown_ref, catalog_ref = match_brightest_stars(unknown_stars, catalog)
-    # get attitude
-    attitude = orient(unknown_ref, catalog_ref)
-    # rotate each star to catalog-referenced coordinates and match by L2 norm
-    index_guesses = []
-    for star in unknown_stars:
-        v = attitude.apply(star['v'])
-        index_guesses.append(np.argmin([np.linalg.norm(catalog_star['v'] - v)
-                                        for catalog_star in catalog]))
-
-    r.send(','.join(map(str, index_guesses))+'\n')
-    r.recvuntil('Left...\n')
-print(r.clean())
+rotated = [dict(v=rotation.apply(x['v']), m=x['m']) for x in refstars_magsorted]
+found_idxes = []
+for star in rotated:
+    found_idxes.append(np.argmin([np.linalg.norm(star['v']-catalogstar['v']) for catalogstar in catalog]))
 ```
 
+It's then trivial to send `found_idxs` back to the challenge as a comma-separated string of indices for each problem sent to us; the server happily sends us the flag after we answer its questions.
+
 ### Full code
-```{.python include=spacebook.py}
+```{.python include=spacebook-original.py}
 ```
 
 ## Resources

aaaa/spacebook/spacebook-original.py

@@ -0,0 +1,54 @@
+import numpy as np
+from pwnlib import tubes
+import time
+import matplotlib.pyplot as plt
+from rmsd import calculate_rmsd
+from scipy.spatial.transform import Rotation
+%matplotlib inline
+
+def read_starfile(data):
+    stars = []
+    for line in data.strip().split('\n'):
+        [x,y,z,m] = [float(s.strip()) for s in line.split(',')]
+        stars.append({'v': np.array([x,y,z]), 'm':m})
+    return stars
+
+with open('./spacebook-golf56788echo/test.txt') as f:
+    catalog = read_starfile(f.read())
+
+TICKET = 'THE_TICKET'
+r = tubes.remote.remote('spacebook.satellitesabove.me', 5015)
+r.send(TICKET+'\n')
+time.sleep(0.5)
+r.recvuntil('Ticket please:\n', drop=True)
+
+for _ in range(5):
+    refstars = read_starfile(r.recvuntil('\n\n').decode())
+
+    refstars_magsorted = sorted(refstars, key=lambda x:x['m'])[::-1]
+
+    catalog_magnitudes = np.array([x['m'] for x in catalog])
+    matches = []
+
+    for idx, star in enumerate(refstars_magsorted):
+        if star['m'] <= 500:
+            break
+        match = np.argmin(np.abs(catalog_magnitudes-star['m']))
+        matches.append(match)
+    print(matches)
+
+    P = np.vstack([x['v'] for x in [catalog[i] for i in matches]])
+    Q = np.vstack([x['v'] for x in refstars_magsorted[:4]])
+    print("rmsd: {}".format(calculate_rmsd.kabsch_rmsd(P,Q)))
+    rotation_mtx = calculate_rmsd.kabsch(P, Q)
+    rotation = Rotation.from_matrix(rotation_mtx)
+
+    rotated = [dict(v=rotation.apply(x['v']), m=x['m']) for x in refstars_magsorted]
+    found_idxes = []
+    for star in rotated:
+        found_idxes.append(np.argmin([np.linalg.norm(star['v']-catalogstar['v']) for catalogstar in catalog]))
+
+    r.send(','.join([str(x) for x in found_idxes]) + '\n')
+    time.sleep(0.1)
+    r.recvuntil('Left...\n')
+print(r.clean())