I recently stumbled upon what might be the most charmingly naive CAPTCHA implementation I’ve ever seen: Fossil SCM’s text-based CAPTCHA. It renders hex digits as ASCII art using unicode block characters, and asks users to type what they see. You can find a live example here.
Here’s what 69B34B04 looks like:
██████ ██████ ████████ ██████ ██ ████████ ██████ ██
██ ██ ██ ██ ██ ██ ██ ██ ████ ██ ██ ██ ████ ████
██ ██ ██ ██ ██ ██ ██ ██ ██ ██ ██ ██ ██ ██ ██
████████ ████████ ████████ ████ ██ ██ ████████ ████ ██ ██ ██
██ ██ ██ ██ ██ ...I recently stumbled upon what might be the most charmingly naive CAPTCHA implementation I’ve ever seen: Fossil SCM’s text-based CAPTCHA. It renders hex digits as ASCII art using unicode block characters, and asks users to type what they see. You can find a live example here.
Here’s what 69B34B04 looks like:
██████ ██████ ████████ ██████ ██ ████████ ██████ ██
██ ██ ██ ██ ██ ██ ██ ██ ████ ██ ██ ██ ████ ████
██ ██ ██ ██ ██ ██ ██ ██ ██ ██ ██ ██ ██ ██ ██
████████ ████████ ████████ ████ ██ ██ ████████ ████ ██ ██ ██
██ ██ ██ ██ ██ ██ ██████████ ██ ██ ██ ██ ██████████
██ ██ ██ ██ ██ ██ ██ ██ ██ ██ ██ ██ ██ ██
██████ ██████ ████████ ██████ ██ ████████ ██████ ██
My immediate thought was to try and write a solver for it for fun, but while doing so I wondered how small the solver could possibly go. Having never done any sort of code golfing before, this seemed like a good excuse to try.
Understanding the Font
Digging into Fossil’s captcha.c, we find a 5*7 bitmap font. Each hex digit is defined as 7 bytes, where each byte represents a row of 5 pixels:
static const unsigned char aFont2[] = {
/* 0 */ 0x0e, 0x13, 0x15, 0x19, 0x11, 0x11, 0x0e,
/* 1 */ 0x02, 0x06, 0x0A, 0x02, 0x02, 0x02, 0x02,
// ... and so on for all 16 hex digits
};
When rendered, each "on" pixel becomes ██ (two block characters) and each "off" pixel becomes two spaces. Characters are separated by two additional spaces, resulting in a 12-character stride per digit.
Version 1: The straightforward approach
My first solver was relatively readable and obvious: pre-render all 16 patterns from the font, then match each digit.
FONT = bytes.fromhex(
'0e13151911110e' # 0
'02060a02020202' # 1
# ... all 16 digits
)
def solve(captcha):
lines = captcha.split('\n')[:7]
result = ''
for pos in range(0, len(lines[0]), 12):
# extract 7-byte pattern
pattern = bytes(
sum(1 << (4-col) for col in range(5)
if lines[row][pos+col*2:pos+col*2+2] == '██')
for row in range(7)
)
char_idx = FONT.find(pattern) // 7
result += '0123456789abcdef'[char_idx]
return result
This works, but it’s fairly bulky. The font data alone is 224 hex characters. Maybe we don’t need the entire font map.
Version 2: Two rows are enough
I wondered if we actually needed every row of every digit. If we can find a pair of rows that uniquely identifies all 16 hex digits, we can ignore the rest.
I wrote a quick script to check all row combinations:
for r1 in range(7):
for r2 in range(r1+1, 7):
patterns = [(font[digit][r1], font[digit][r2]) for digit in range(16)]
if len(set(patterns)) == 16:
print(f"rows {r1},{r2} are unique!")
Rows (0,3) and (3,6) both seemed to work. When doing my experiments, I attempted everything with both options, but the final most optimal result ended up being (3,6) in the end.
This reduces our pattern from 35 bits (7 rows * 5 bits) to just 10 bits (2 rows * 5 bits).
With 10-bit patterns, our values range from 46 to 990. A direct lookup table would need 991 entries with only 16 used, which is incredibly wasteful.
Instead, I searched for a modulus where all 16 patterns give unique remainders:
patterns = [814, 66, 95, 206, 578, 46, 974, 136,
462, 494, 561, 990, 526, 572, 927, 976]
for m in range(16, 100):
if len(set(p % m for p in patterns)) == 16:
print(f"mod {m} works!")
break
# Output: mod 43 works!
Now I can build a sparse 43-character lookup string:
lookup = ['?'] * 43
for pattern, char in zip(patterns, '0123456789abcdef'):
lookup[pattern % 43] = char
# Result: ?ba5???7?2c??d?????4?9?1e???6?f?8?3?????0??
The ? characters are never accessed, they’re essentially just padding so the lookup works.
Version 4: Let’s go golfing
Here’s a readable version of what we have so far:
def solve(captcha):
LOOKUP = '?ba5???7?2c??d?????4?9?1e???6?f?8?3?????0??'
lines = captcha.split('\n')
result = ''
for pos in range(0, len(lines[0]), 12):
pattern = 0
for row in (3, 6):
for col in range(5):
if lines[row][pos + col*2 : pos + col*2 + 2] == '██':
bit_position = 5 * (row < 4) + 4 - col
pattern |= 1 << bit_position
result += LOOKUP[pattern % 43]
return result
I browsed the code golfing Stack Exchange for some inspiration and found a few tricks we could apply here.
Trick 1: Walrus operator for assignment-in-expression
s = lambda t: (L := t.split('\n')) and ''.join(...)
The walrus operator (:=) assigns L and returns it. Since a non-empty list is truthy, and evaluates and returns the right side.
Trick 2: Single-character pixel detection
Instead of lines[row][pos+col*2:pos+col*2+2] == '██', we can check just one character:
lines[row][pos + col + col] > '!'
The reason this works is that the block character █ has the unicode value 9608 and space is 32. ! is 33, which means char > '!' is True for blocks, False for spaces. This saves a mere one character by not having to use the comparison operator ==.
Trick 3: Bit position formula
Since boolean values map to 0 and 1 when used as integers, we can use a comparison to pack the bit positoin calculation into one formula for both rows: 5*(r<4)+4-c.
So for both rows:
- When
r=3:5*True + 4 - c=5 + 4 - c= bits 9,8,7,6,5 - When
r=6:5*False + 4 - c=0 + 4 - c= bits 4,3,2,1,0
Result: 187 characters
s=lambda t:(L:=t.split('\n'))and''.join('?ba5???7?2c??d?????4?9?1e???6?f?8?3?????0??'[sum((L[r][p+c+c]>'!')<<5*(r<4)+4-c for r in(3,6)for c in range(5))%43]for p in range(0,len(L[0]),12))
This was pretty good compared to the original.
Version 5: Why 43?
At this point I wondered whether could we shrink the lookup table further by transforming the pattern values.
The modulus of 43 felt a bit arbitrary. What if we XOR the pattern with some constant before taking the modulo? This might "scramble" the values into a smaller range.
I brute-forced it:
patterns = [814, 66, 95, 206, 578, 46, 974, 136,
462, 494, 561, 990, 526, 572, 927, 976]
for xor_val in range(1, 2048):
transformed = [p ^ xor_val for p in patterns]
for m in range(16, 43):
if len(set(t % m for t in transformed)) == 16:
print(f"^{xor_val} %{m} works")
break
This resulted in a few valid options that were smaller, but the smallest result ended up being ^293 %21. By XORing the result with 293 before taking mod 21 still gives unique values for all 16 digits. The lookup table shrinks from 43 to just 21 characters:
2f1?8e?b374a6c95d??0?
The tradeoff is that we need parentheses around the XOR operation (since ^ has lower precedence than %), adding a few characters of syntax, but the 22-character reduction in the lookup table more than compensates.
The final, fully golfed version is only 171 characters long:
s=lambda t:(L:=t.split('\n'))and''.join('2f1?8e?b374a6c95d??0?'[(sum((L[r][p+c+c]>'!')<<5*(r<4)+4-c for r in(3,6)for c in range(5))^293)%21]for p in range(0,len(L[0]),12))
Annotated:
s = lambda t: (
(L := t.split('\n')) # split into lines, assign to L
and # L is truthy, so evaluate right side
''.join(
'2f1?8e?b374a6c95d??0?'[ # lookup table
(
sum( # sum of bit contributions
(L[r][p+c+c] > '!') # 1 if block char, 0 if space
<< 5*(r<4) + 4 - c # shift to correct bit position
for r in (3, 6) # only rows 3 and 6
for c in range(5) # 5 columns per row
) ^ 293 # XOR to scramble values
) % 21 # modulo for table lookup
]
for p in range(0, len(L[0]), 12) # step through each character position
)
)
Final thoughts
I hope I haven’t caused the Fossil people any extra work by having to scramble and come up with a new CAPTCHA system! They do seem to admit that their CAPTCHA isn’t exactly the most secure:
/*
** This file contains code to a simple text-based CAPTCHA. Though easily
** defeated by a sophisticated attacker, this CAPTCHA does at least make
** scripting attacks more difficult.
*/
Luckily, they do seem to be actively using a proof-of-work approach for deterring bots which you can see in robot.c.
As for the code golf part, it was fun trying to come up with tricks and techniques to optimize for code size instead of performance or any other metric I usually optimize for. I’m sure that seasoned golfers can spot some obvious optimizations that I missed, but 171 characters seemed like a good stopping point for me.